Microsoft has shared a temporary fix for ongoing gaming issues caused by Windows 11 updates released during the August 2026 Patch Tuesday. On impacted PCs, users reported games crashing or failing to launch, as well as game freezes, "EXCEPTION_ACCESS_VIOLATION" errors, and even unexpected system restarts. When it confirmed it was investigating this known issue on Wednesday, Microsoft said it affects games like ARC Raiders, MARVEL Tōkon: Fighting Souls, and The Finals on systems running Windows 11 24H2 and 25H2. "Following the release of Windows updates on August 11, 2026 (KB5121003) and later, Microsoft received reports of issues involving inability to run games as expected," Microsoft noted. In a Thursday update, the company linked the gaming issues to drivers or components installed by RGB devices on affected Windows systems.
TikTok will pay $400 million to settle U.S. claims that it violated child privacy laws by collecting data from users under 13. The U.S. Department of Justice announced that TikTok will pay $400 million to settle a 2024 lawsuit over children’s privacy. “Today, the Department of Justice announced a $400 million settlement with TikTok, ByteDance, and affiliated entities (TikTok) resolving litigation concerning compliance with the Children’s Online Privacy Protection Act and its implementing regulations (COPPA).” reads the press release published by DoJ. “Under the settlement, TikTok will pay $300 million immediately and an additional $100 million upon entry of an order vacating a prior consent decree entered against TikTok’s predecessor, Musical.ly. The settlement represents one of the largest recoveries ever obtained in a COPPA case.” TikTok will pay $300 million immediately and another $100 million after a court order removes an earlier consent decree involving Musical.ly. The 2024 case, brought by the DoJ and FTC, accused TikTok of knowingly allowing children under 13 to create accounts and illegally collecting data from children using Kids Mode. Since the Justice Department filed its lawsuit against TikTok in 2024, the company has made major changes to its ownership, management, compliance, and privacy practices. It has also introduced stronger safeguards for younger users, improved age controls, and expanded parental oversight. The DOJ said these measures have advanced the goals of its case and strengthened protections for millions of U.S. families. The settlement reflects a focus on practical results, securing a significant recovery while recognizing TikTok’s compliance improvements. The case was filed in California and handled by the DOJ’s Civil Division following a referral from the FTC. “This settlement is a major victory for American children and parents,” said Associate Attorney General Stanley E. Woodward Jr. “The Department’s priority is ensuring that children are protected online and that companies entrusted with their personal information meet their legal obligations. This resolution secures a substantial recovery while reinforcing the protections that families expect and deserve.” TikTok has faced regulatory scrutiny over children’s privacy before. In September 2023, Ireland’s Data Protection Commission fined the company €345 million for breaching the GDPR through its handling of children’s personal data. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, privacy)
iAuthFlow v2 phishing toolkit uses a phished Google session to enroll an attacker-controlled passkey that survives password resets. Abnormal Security researchers have published an analysis of iAuthFlow v2, a phishing toolkit sold on a Russian-language cybercrime forum for $10,000 base price. The author also offers for sale additional capability modules separately. The headline feature is not the phishing itself. It’s what happens after the phishing succeeds. “Once the target completes a phishable Google login, the toolkit uses the authenticated session to enroll a passkey controlled by the operator.” reads the report published by Abnormal Security. “In the seller’s recorded demonstration, the account owner later changes their password, invalidating the active session—but the operator authenticates with the newly enrolled passkey and returns to the mailbox.” That’s the architecture. The phishing flow gives the attacker a temporary window. iAuthFlow v2 uses that window to create a permanent key that doesn’t close when the window does. The toolkit uses a browser-in-the-middle attack. The victim sees what looks like a real Google login page, while iAuthFlow v2 runs another browser on the attacker’s server. Everything the victim types, including their email, password and two-factor code, is sent to that remote browser, which logs in to Google. The victim provides the credentials, while the attacker gets the authenticated session. In the demo, the fake login page used a trycloudflare.com subdomain, giving the link a valid TLS certificate and a more trustworthy appearance. Once the relay gives the attacker’s browser Google’s session cookies, iAuthFlow v2 holds the target on a “Verification, Processing” page while the toolkit works inside the account. This pause is a named state in the software, not a recording artifact. The session log timestamps tell the story precisely: login at 21:37:18, passkey created and saved at 21:37:24. Six seconds to establish persistent access. The passkey module navigates the target’s Google passkey settings through the authenticated browser and requests a new credential. Google may ask for identity re-verification before allowing the enrollment; the demo shows the toolkit handling this. The enrolled passkey is then stored on the attacker’s side, and the toolkit records “Passkey created and saved.” “The log records “Passkey created and saved.” At this point, the operator no longer has only the authenticated session created through the phishing flow.” continues the report. “The newly enrolled passkey is a separate authentication credential registered to the target’s Google account. The subsequent demonstration shows Google offering that passkey during a later sign-in, consistent with the operator retaining the credential needed to use it.” This is more serious than simply stealing a session cookie because a password reset does not remove a passkey. Changing a Google password ends active sessions, revokes app passwords and invalidates some OAuth tokens. A passkey is different: it is a separate cryptographic credential linked to the account and remains active until it is manually removed. The demo shows the risk clearly. After the victim changes their password, the attacker’s session stops working. But the attacker can choose “Try another way,” use the passkey they previously added and regain access to the mailbox. The victim may have no idea this happened. Abnormal notes a technically plausible mechanism for how iAuthFlow v2 stores and uses the passkey: Chromium’s software-based virtual authenticators, which support WebAuthn registration and retain private keys without requiring the target’s physical device. The researchers don’t confirm this is what the toolkit uses, since the demonstration doesn’t reveal the implementation. What they confirm is that the behavior shown is consistent with how passkeys work, and there’s an available path to produce it. The toolkit targets Google in the build Abnormal examined, but the seller advertises versions for Microsoft, iCloud, and LinkedIn. The same post-authentication persistence logic applies wherever passkeys can be enrolled. Containment after an iAuthFlow v2 compromise needs to go further than incident response teams are often used to going. “That cleanup is particularly important with iAuthFlow v2 because neither a password reset nor session revocation removes an attacker-enrolled passkey.” states the report. “Restore the account only after unauthorized authentication methods and other persistence mechanisms have been removed.” The full sweep should cover unauthorized passkeys and security keys, malicious Gmail filters and forwarding rules, delegated access, OAuth grants and app permissions, and recovery settings. Organizations running Google Workspace can use the Security Investigation Tool to audit the account before declaring it clean. The best way to prevent these attacks is to rely on authentication methods that cannot be easily stolen through phishing. WebAuthn-based authentication is tied to the real website, so stolen passwords or codes cannot be used through a relay attack. Google Workspace can enforce this with the “Only security key” option for 2-Step Verification and through the Advanced Protection Program. These settings also disable app passwords, which the toolkit may target on less protected accounts. The toolkit’s price and professional sales channels suggest this is an ongoing business, not a one-time release. If a Google account is compromised but appears clean after a password reset, security teams should also check the account’s passkeys and security keys before closing the case. “iAuthFlow v2 illustrates how phishing has evolved beyond stealing credentials or even hijacking a single authenticated session. Once an attacker gains legitimate access to an account, that access can become a starting point for establishing new authentication methods, modifying account settings, and creating other forms of persistence.” concludes the report. “Response and recovery cannot end with a password reset or session revocation. Organizations must also examine what changed after authentication—especially newly enrolled credentials, recovery methods, OAuth grants, and mailbox settings—and remove anything the attacker left behind. “ Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, iAuthFlow v2 phishing toolkit)
The ToxicPanda Android malware has evolved with new malicious functionality, expanding its targeting to 349 applications and adding support for 167 remote commands. The malware now requests VPN service permissions to create a local interface that allows it to control network traffic passing through it. The feature enables ToxicPanda 2.0 to block communication from Google Play and Google Play Services. Control at the network level permits the malware to interfere with various security checks and actions, such as app verifications, updates, Play Protect communication, or legitimate disruptions designed to protect users. After obtaining VPN service permissions, ToxicPanda 2.0 blocks communications to Google Play before extracting and installing its payload, then requests Accessibility Service permissions.
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ToxicPanda 2.0 Gets a Major Upgrade, Expanding Attacks Across 16 CountriesMalware Hijacks Android Car Head UnitsCritical Flaw in NASA/JPL Open-Source Spacecraft Command Software Allowed Unauthenticated Command ExecutionU.S. CISA adds Zimbra Collaboration Suite (ZCS) flaw to its Known Exploited Vulnerabilities catalogYour Shredded Visa Card May Still Work at the CheckoutSix Maximum-Severity Flaws Found in Cisco ProductsFake Conferences, OAuth and WhatsApp: Inside Russia’s New Espionage TacticsGitLab Warns of Active Exploitation of Critical GraphQL FlawPoland’s CERT Warns of Active Exploitation of Critical Zimbra Collaboration Suite FlawU.S. CISA adds TrueConf Server flaws to its Known Exploited Vulnerabilities catalogCl0p Targets 40+ Organizations Through PTC Windchill FlawManic: The Android Malware That Exfiltrates Data Even When the Phone Is OfflineNSA, CISA, FBI, DOE, and EPA Warn of Active AI-Assisted Attacks on Siemens S7 PLCsU.S. CISA adds an MLflow flaw to its Known Exploited Vulnerabilities catalogUS Indicts 17 Iranians Over Years-Long Cyber Espionage CampaignStopAndProtect Turns 2,000 Hacked WordPress Sites Into a Criminal NetworkInside Operation CameraSwarm: How One Actor Took Over 14,000 Dahua CamerasMicrosoft Tracks MacSync Stealer by Its Behavior, Not Its Domains50,000 Stripe Secrets Leaked in Public CodeU.S. CISA adds Apple macOS, Microsoft SharePoint, Broadcom VMware vCenter, and Microsoft IKE flaws to its Known Exploited Vulnerabilities catalogHackers Expose Data of 1.2 Million Heights Finance CustomersProject noRecognition: Teaching AI to Fool Surveillance CamerasGitLab Patches Critical Unauthenticated GraphQL VulnerabilityU.S. CISA adds a Ray-Project Ray flaw to its Known Exploited Vulnerabilities catalogNew Mirai-Based Evooo1Bot Botnet Targets Linux DevicesSafePal Says 39,798 Customers Hit by Data BreachLiteLLM Supply-Chain Attack – Technology, Banking and Healthcare the Most AffectedInvisible AI Prompts Trigger Court SanctionsMcDonald’s Employee Data Appears in Leak, Seller Claims 1.7M Records StolenAkira Ransomware Uses Safe Mode to Bypass EDRDDoS Attacks Cause Major Threema OutagesMustang Panda Upgrades CoolClient With a Kernel RootkitSophisticated Cyberattack Exposes Data of 678,000 French TaxpayersAPT36 Suspected in PATCHCORD Espionage Campaign Using Google Sheets C2 International Press – Newsletter Cybercrime McDonald’s employee data listed for sale in wider Entra campaign $7 Million in Expired Domains Fuel a Streaming Empire with a Malware Secret Live Stripe keys for 659 merchants, published for free Clop Returns with Custom Implant in Mass-Extortion Campaign Justice Department Secures $400M Settlement with TikTok and ByteDance to Resolve Children’s Privacy Litigation Malware Akira Hits Safe Mode: Ransomware Rebooting Around EDR Hunting MacSync Stealer infrastructure through behavioral pivots Manic: Blend between Banking Malware & Spyware The ToxicPanda Never Sleeps: ToxicPanda 2.0 Prepares its Next Strike on Mobile The invisible passenger in your car Grandoreiro goes north: From Brazil to Mexico with a new DLL sideloading campaign Hacking Large-scale DDoS attacks disrupted Threema secure messaging service The LiteLLM Supply-Chain Attack — TeamPCP “SANDCLOCK” CI/CD Credential-Harvesting Campaign via a Backdoored Trivy GitHub Action Actively exploited vulnerability in Zimbra Collaboration Suite AI-assisted tool helped secure satellite communication system after 2022 Russian hacking Expired credit cards revived by researchers to make unauthorized payments CDN Tsunami: Exploiting HTTP/3-HTTP/1.1 Conversion for DoS Attacks When the NASA Ground Station Has No Lock on the Door: Unauthenticated Command Execution in AIT-GUI (GHSA-p9r8-2q67-fp86) Zero-click Grok data theft: Cryptographic Context Injection attack leaks chat histories Intelligence and Information Warfare Operation CameraSwarm: Over 14,000 Dahua cameras compromised across Ukraine and Russia 17 Iranians Charged with Conducting Massive Cyber Theft Campaign on Behalf of the Islamic Revolutionary Guard Corps and Other Iranian Entities Defending Against an Active Threat to Siemens S7 Series PLCs Rust Supply Chain Attack on arrayref: Significant Overlap with DPRK Campaigns Going with the Flow(s): Distinct Clusters Target Individuals of Interest to Russia SilkParasite: Tracking a China-Nexus APT Across Central Asia Revealed: Cyber spies used malware from GitHub to hack EncroChat cryptophone network Cybersecurity France probes unprecedented cyberattack after tax data of 678,000 users stolen Person Hides Prompt Injection in Legal Filing Telling AI to Side With Them SafePal Unauthorized Access To A Subset Of Customer Order Information This ‘adversarial’ pattern can prevent surveillance cameras from detecting you France’s cybersecurity problem demands strong political will The Powerful Chinese AI Model Experts Warned About—and Waited for—Is Here OpenAI president says companies should do 10 things ASAP to defend against AI cyber threats Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, newsletter)
New Cryptographic Context Injection technique bypasses AI guardrails via AES-encrypted payloads, leaking full Grok chat histories zero-click Adversa AI researcher Rony Utevsky devised a new attack technique, called Cryptographic Context Injection, that bypasses AI safety filters by sending instructions as AES-encrypted ciphertext and tricking the model into decrypting them inside its own code execution runtime. The technique was demonstrated against two live production systems: xAI’s Grok and Google’s Gemini. “Cryptographic Context Injection hides malicious instructions inside AES-encrypted text so guardrails can’t read them, then tricks the AI into decrypting and trusting them as its own.” reads the report published by Adversa AI. “In Grok, an ordinary “summarize this page” steals the user’s chat data with no click or warning. In Gemini, it produces content the model normally refuses. Both are live production systems.” The Grok case is the more serious of the two. A user asks Grok to summarize a webpage containing an encrypted payload and instructions to decrypt it. Grok visits the page, decrypts the payload in its Python sandbox, and follows the hidden instructions. It then accesses the user’s private session data, including their name, location, subscription plan, and full chat history, and puts this information into a URL that it opens automatically. The user receives no warning and does not need to click anything. The key technical distinction from earlier cipher-based prompt injection work is what happens during decryption. “Static safety guardrails classify inputs as text; they do not execute them. An attacker ships ciphertext along with the key material and an instruction to decrypt it, and the model runs that decryption inside its own code execution sandbox.” continues the report. “Everything a guardrail’s scanner would need is right there on the page, but recovering the plaintext means running PBKDF2 and AES-256-GCM, which no content classifier does at inspection time. “ Prior techniques like CipherChat and CodeChameleon used substitution ciphers, XOR, or base64, schemes the model can decode natively in its own context without an interpreter. AES-256-GCM can’t be decoded that way. Recovery requires the runtime, and that’s the channel the attack depends on. Once the runtime decrypts the payload, the attacker’s instructions appear as the output of code the model just ran, not as untrusted external content. “The runtime execution launders attacker-controlled data into trusted instructions the agent will act upon. That is how the attack got its name: cryptography helps fabricate trusted context for the agent.” states the report. “The same cryptographic backbone works whether the injection is direct or arrives indirectly, for example through the browsing channel.” The attacker payload inherits a credibility the same text would never get if pasted directly into the prompt. The Grok demo hides the data theft behind what looks like a normal request. The payload tells the model to create a “decryption key,” but the key is actually a template containing the user’s private data, such as their name, location, subscription tier, and chat history. Grok then uses this information as a URL parameter when opening an attacker-controlled website to “fetch additional context.” The data is sent through the URL as part of a seemingly normal web request. Adversa said the attack was still reproducible on August 19, 2026. Adversa traces the structural problem to Grok’s agentic framework, not to any model-layer failure. The framework lets instructions from an untrusted external page drive the invocation of a privileged, internet-connected tool. It allows private session metadata and conversation history to be resolved into the inputs of outbound calls. It enforces no egress boundary or consent gate on that path. Adversa’s description maps cleanly to SQL injection: a system that can’t distinguish its own trusted state from attacker-supplied data flowing through the same channel. The Gemini case uses the same basic trick but in a different way. A prompt asks Gemini to run a Python script that decrypts some data and returns a small JSON result. Instead, the decrypted data contains a fake Python error message with hidden instructions designed to bypass Gemini’s safety rules. Because Gemini treats the sandbox output as trusted context, those instructions can influence its behavior. Adversa used the technique to make Gemini generate detailed instructions for building an incendiary device. A modified version also exposed Gemini’s system instructions. Adversa reported the Grok issue to xAI on June 3, 2026, but received no further response after the initial acknowledgment. The attack was still working shortly before publication. The Gemini issue was not formally reported because Google’s bug bounty excludes jailbreaks. Adversa said Gemini’s vulnerability rate has nevertheless dropped sharply since June. For defenders, Adversa’s guidance is that nothing about this attack requires a fix at the model layer. Every control that bounds it sits in the harness around the agent. Untrusted content should be processed in a context with no tools and no credentials, returning only structured data to the privileged context. Outbound network calls and writes outside the workspace should require explicit confirmation with fully resolved arguments visible before approval. Per-session tool traces with resolved arguments should be logged, because without them there’s no forensics and no detection. Detection should alert on sequences, not individual payloads: untrusted content enters context, code executes, agent contacts a host outside its normal dependency graph. That chain is the signal, not any single ciphertext blob. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Cryptographic Context Injection)
ToxicPanda 2.0 targets 349 financial apps and abuses Android Wireless Debugging to gain deeper device access and steal banking credentials. ToxicPanda used to be a Europe-focused nuisance targeting a manageable list of banks. That version is gone. Zimperium’s zLabs team just documented ToxicPanda 2.0, and the numbers alone tell the story: 349 targeted financial institutions across 16 countries, up from 16 apps in the previous version, plus a command set that ballooned to 167 remote instructions. The infection starts with a fairly standard trick dressed up in a new coat of paint. The malware poses as a dropper, requesting VPN permissions through a fake installation screen, then quietly uses that access to block communication from Google Play Protect while it decrypts and installs the real payload hiding inside the app’s own asset files. Once installed, it leans on Android’s Accessibility Service, the same feature legitimate screen readers and automation tools rely on, to see and interact with everything happening on the victim’s screen. ToxicPanda was once a malware mainly targeting a small number of European banks. That has changed. Zimperium’s zLabs team has documented ToxicPanda 2.0, which now targets 349 financial institutions in 16 countries, compared with just 16 apps before. It also has 167 different commands that attackers can send remotely. The attack starts with a common trick. The malware pretends to be a legitimate app and asks for VPN permissions through a fake installation screen. It then uses this access to block Google Play Protect while secretly installing the real malware hidden inside the app’s files. Once installed, ToxicPanda abuses Android’s Accessibility Service. This feature is normally used by legitimate tools such as screen readers, but the malware uses it to monitor the victim’s screen and interact with apps and data on the device. “By abusing the Android Accessibility Service, threat actors can steal every UI element on the screen, alongside an overlay-based credential theft mechanism targeting 349 financial institutions, compared to the previous version, which targeted only 16 banking applications, the latest iteration demonstrates a significant expansion in targeting scope and capabilities.” reads the report published by Zimperium’s zLabs. “Several commands previously identified as unimplemented in Cleafy’s analysis are now fully operational, expanding the malware’s remote control and fraud capabilities.” What sets this version apart isn’t just scale, it’s a genuinely new privilege escalation trick built around a feature most people have never touched: Android’s Wireless Debugging framework. The malware automates the entire process of turning it on, tapping the build number seven times to unlock developer options, toggling wireless debugging, and then scraping the six-digit pairing code straight off the screen using accessibility permissions. From there it performs the actual cryptographic pairing handshake itself, gaining shell-level access to the device without the victim ever realizing developer mode got switched on. ToxicPanda was once a malware mainly targeting a small number of European banks. That has changed. Zimperium’s zLabs team has documented ToxicPanda 2.0, which now targets 349 financial institutions in 16 countries, compared with just 16 apps before. It also has 167 different commands that attackers can send remotely. The attack starts with a common trick. The malware pretends to be a legitimate app and asks for VPN permissions through a fake installation screen. It then uses this access to block Google Play Protect while secretly installing the real malware hidden inside the app’s files. Once installed, ToxicPanda abuses Android’s Accessibility Service. This feature is normally used by legitimate tools such as screen readers, but the malware uses it to monitor the victim’s screen and interact with apps and data on the device. The real danger comes from its ability to use Android Debug Bridge (ADB). Once connected, ToxicPanda can run commands through ADB without showing the usual permission requests. This allows it to give itself more permissions, remove Android restrictions on background activity, enable important components without the user knowing, and maintain access to the device. “The malware also introduces an automated click-based mechanism to abuse Android Wireless Debugging (ADB), enabling privilege escalation and shell-level access on compromised devices. Additionally, it can steal lock screen credentials by placing overlays on top of the lock screen.” continues the report. The credential theft itself runs on two separate tracks. For banking and crypto apps specifically, the malware watches which app the victim opens, matches it against a list of 349 targets, and either overlays a fake login screen or deploys an invisible transparent layer to capture every touch and PIN entry directly. Separately, it can now overlay a convincing fake version of the phone’s own lock screen to steal the device PIN, pattern, or password outright, which hands attackers a way back in even after the initial infection window closes. Several capabilities that security firm Cleafy had previously flagged as unfinished in an earlier ToxicPanda variant are now fully working. The malware can automatically click through OEM-specific permission dialogs across Xiaomi, Samsung, Huawei, and other manufacturers’ customized Android builds, request Device Administrator privileges using a fake “system service” prompt, and even remotely force-reset a victim’s lock screen password using legitimate Android device management APIs. It can also load an attacker-controlled webpage inside a full-screen overlay on command, a feature that simply didn’t exist in prior versions. Distribution has shifted too, with samples now getting served from Amazon AWS-hosted storage buckets rather than whatever ad-hoc infrastructure earlier campaigns used. “The updated campaign also reveals a shift in distribution methods, with ToxicPanda 2.0 samples being delivered through Amazon AWS-hosted buckets, indicating the attackers are leveraging cloud infrastructure for malware delivery.” states the report. Using major cloud providers for malware delivery isn’t new, but it does complicate blocking efforts, since flagging an entire AWS IP range as malicious tends to take down a lot of legitimate traffic along with it. None of this requires a sophisticated zero-day, which is honestly the more unsettling part. Every capability here abuses a feature Android ships intentionally, Accessibility Services, Wireless Debugging, Device Administrator APIs, all designed for legitimate accessibility and enterprise device management. “As mobile banking threats like ToxicPanda become increasingly sophisticated, conventional signature-based security layers are no longer sufficient to protect enterprise mobile endpoints.” concludes the report. If you’re responsible for securing mobile endpoints, this is less a “patch something” problem and more a “detect abnormal use of normal features” problem, and that’s a considerably harder thing to build detection around. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, ToxicPanda 2.0)
A supply-chain attack targeting Android-based car head units is using a legitimate device-update app to spread malware that enlists compromised devices in a proxy botnet or uses them for ad fraud. Kaspersky researchers analyzed the malware and attributed the operation to the MoYu group, a threat actor previously associated with the BadBox malware botnet. The researchers note that this is the first documented case of a malware infection chain specifically created for the targeted car head unit. MoYu's operation targets systems from DoFun, a Chinese automotive software and hardware provider owned by Shenzhen Driving Control Technology Co., Ltd. DoFun is an automotive software, cloud services, and hardware provider that sells generic Android-based head units, which act as the command center for a car's infotainment, navigation, and settings systems.
Malware is abusing car infotainment updates to install proxy software, turning Android head units into nodes for the BADBOX network. Kaspersky researchers found something in June 2026 that made them stop and look twice: an Android app with no interface at all, installed like any ordinary app but making zero effort to disguise itself as legitimate. Their report documents the first known malware infection targeting car head units, the Android-based infotainment and control systems built into many modern vehicles, spread through the vehicle’s own official update mechanism. Head units run Android for practical reasons, since manufacturers can build on existing source code and add their own custom system apps during production. That flexibility cuts both ways. Because head units are just Android devices under the hood, most apps built for smartphones can technically run on them too, including malware, even though something like a banking trojan would be wasted effort on a device nobody uses for mobile banking. Kaspersky researchers found something unusual in June 2026: an Android app with no visible interface that was installed like a normal app but did not try to look legitimate. Their report describes what they say is the first known malware infection targeting car head units, Android-based systems used for infotainment and vehicle controls, delivered through the car’s official update system. “We identified new Android malware: a multi-stage downloader whose ultimate purpose is ad fraud and creation of a proxy botnet.” reads the report published by Kaspersky. “The malware spread through the built-in updaters of Android-based automotive head unit firmware. This is the first documented case of malware found on a car head unit with an infection chain specific to that type of device.” Car head units often use Android because it is flexible and lets manufacturers add their own software. But this also creates a security risk. Since these systems are basically Android devices, many apps designed for smartphones can also run on them, including malware. The infection chain here starts inside TWCore, a completely legitimate system app responsible for analytics and firmware updates on DoFun head units. An MQTT message broker sends TWCore instructions about which APK files to download and install, and a specific configuration flag called installNotExists controls whether the app checks if something is already installed before pushing it. “TWCore only checks whether an app is already installed on the device when installNotExists = false The APK file is downloaded to <TWCore external cache dir>/push/apk/ for installation.” which means setting that flag the other way turns a routine update channel into a silent installation pipeline for anything the attackers want to push. What gets installed through that channel is a small dropper called JarService, carrying zero user interface and doing nothing but decrypting and loading the next stage. That stage is a loader that phones home to a command server, reports basic device details, and receives a download link for the actual payload, a third-stage module researchers found could be pulled in at least seven different versions simply by trying different version numbers in the download URL. That third stage turns out to be a clicker and reverse proxy component, checking in with its server every 90 minutes by default and waiting for new instructions. “In this stage, the malware sends a POST request to /cpc/api/task every 90 minutes by default, containing information about the infected device (display resolution, device model, the SSID of the connected Wi-Fi network, MAC address, and so on) along with the Trojan’s configuration version.” continues the report. “If the configuration is outdated, the C2 server returns an updated configuration containing new C2 addresses and new paths for sending HTTP requests.” The command system behind the malware is more powerful than you might expect from something running silently on a car’s dashboard. Researchers found nine commands, including ones that can change the clipboard, send HTTP requests, load web pages, and run JavaScript. In practice, attackers mainly used two: one to download and run new code, and another to send web requests. The extra module they deployed, called “zhima,” was a reverse proxy. This means the main goal was not to attack or control the car. Instead, the attackers wanted to use infected cars’ internet connections as part of a larger proxy network. Tracing the malware’s naming conventions and infrastructure led researchers to attribute the campaign, with high confidence, to MoYu Group, an actor connected to the BADBOX botnet that’s been documented previously by other researchers. A thread inside the second-stage loader carried the internal name “mosdk-host-loader,” which pointed toward malware previously found on TV set-top boxes tied to the same group, and overlapping network infrastructure independently spotted by a separate research team around the same time backed up the connection. The command system behind the malware is more powerful than you might expect from something running silently on a car’s dashboard. Researchers found nine commands, including ones that can change the clipboard, send HTTP requests, load web pages, and run JavaScript. In practice, attackers mainly used two: one to download and run new code, and another to send web requests. The extra module they deployed, called “zhima,” was a reverse proxy. This means the main goal was not to attack or control the car. Instead, the attackers wanted to use infected cars’ internet connections as part of a larger proxy network. There is also a strange detail in the network’s infrastructure. The proxy service’s admin panel allows people to create accounts if they have a valid invite code. Its copyright text and login page also look similar to those used by at least two commercial residential-proxy services. This suggests the network may be linked to a business-like proxy service, while also using infected cars to provide internet connections. BADBOX has survived several takedown attempts by researchers and law enforcement. This campaign shows why: the people behind it keep changing how they spread the malware and are moving into new types of devices. Cars are now joining smart TVs and set-top boxes as devices that can be quietly added to a botnet. As cars become more like computers, they also need the same kind of security protection. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Android Car)
A critical flaw (CVSS 9.4) in NASA/JPL’s AIT-GUI let anyone send unauthenticated commands to spacecraft instruments. Cycode researchers found that AIT-GUI, the browser-based operator console in NASA/JPL open-source AMMOS Instrument Toolkit, shipped with no authentication, no session checks, and no CSRF protection on any of its state-changing endpoints. “AIT-GUI, the web front end of NASA/JPL’s open-source AMMOS Instrument Toolkit, starts an HTTP server with no authentication, no authorization, and no CSRF protection on any of its state-changing endpoints.” reads the report published by Cycode. “Anyone who can reach the port, or any website an operator merely visits in a browser, can: Issue arbitrary commands via POST /cmd Run server-side scripts via POST /script/run Execute command sequences via POST /seq“ The vulnerability is tracked as GHSA-p9r8-2q67-fp86, rated Critical (CVSS score of 9.4), and fixed in AIT-GUI 2.5.2. AMMOS (Advanced Multi-Mission Operations System) is an open-source framework used by NASA/JPL and other missions to control spacecraft and instruments, send commands, and process the data they send back. AIT-GUI is the web interface operators use to do this in real time. Sending a command through this software is not like filling out a simple online form. The vulnerability isn’t one thing. It’s four ordinary web weaknesses that compose into something with unusual consequences. The first is that the server reads its configured host setting into a variable and then ignores it, binding instead to 0.0.0.0, which means all network interfaces. An operator who sets host: localhost to keep the console on the loopback gets a server exposed to the entire reachable network anyway. The second and third weaknesses follow from the first. There’s no login requirement, no session gate, no CSRF token, and no cross-origin restriction on any route. POST /cmd takes whatever arrives in the command field, parses it, and hands it directly to the command bus: no check, no validation, nothing between the network and the hardware. The fourth weakness lives on POST /seq and POST /script/run, which build filesystem paths by joining raw user input onto a root directory with no confinement. A seqfile value of ../../../../something resolves outside the intended sequence directory. The researchers note that the correct confinement check already exists in the same codebase, on a sibling route called /scripts/load; the safe pattern was already written, just not applied consistently. The CSRF risk is especially serious because a firewall does not stop it. Browsers can send certain form requests from another website without first checking with the target site. So, if an operator opens a malicious page in the same browser they use for the console, it could send commands such as POST /cmd, POST /seq, or POST /script/run. The attacker does not need direct access to the system or its network port—they only need the operator to open a malicious link. Cycode’s research team used a combination of AI-assisted code analysis and human validation to find and confirm the issues. The AI handled the initial codebase review, flagging recognizable patterns: state-changing routes with no auth anywhere in their call path, user input flowing from a request parameter into a subprocess call without sanitization, and a configuration value that was read and then silently discarded. The human researcher then confirmed each pattern was exploitable and reduced each to a working proof-of-concept, including a self-contained CSRF demonstration that drove a real headless browser and recorded zero network preflights. That second step matters. A pattern match points to a candidate; a reproduced exploit confirms the finding is real. Cycode says explicitly it only reports the second kind. “More broadly: operational and ground-system software inherits the same web weaknesses as everything else, but with a far higher cost of failure. Auth, CSRF defense, and input confinement are not optional extras on a panel that commands hardware.” concludes the report. The fix is in AIT-GUI 2.5.2. Operators should upgrade immediately and verify the console port is not reachable from untrusted networks. Anyone who ran an exposed instance before the patch should treat it as a reason to audit command and sequence history, since an unauthenticated POST leaves no user-level trace by design. Maintainers hardening deployments should add authentication and CSRF protection to the command, script, and sequence routes; bind the server to the configured host instead of 0.0.0.0; and apply the existing path-confinement logic from /scripts/load to /seq and /script/run. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, NASA/JPL)
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