An unpatched vulnerability in Calix GS7 XGS (GS5239XG) residential routers used by multiple U.S. broadband providers allows remote, unauthenticated attackers to create port-forwarding rules that can expose local network devices to the public internet.
Hackers are attempting to exploit two critical authentication bypass vulnerabilities in the miniOrange SAML 2.0 Single Sign On plugin for WordPress that can be used to forge SAML responses and log in as administrators. The miniOrange SAML SSO plugin turns a WordPress site into a SAML service provider, letting users log in through corporate identity platforms such as Microsoft Entra ID, Okta, Google Workspace, or OneLogin instead of separate WordPress credentials. Created by Xecurify, miniOrange is a family of seven plugins, with a free version that has 10,000 downloads and 30,000 customers for the other six. The two vulnerabilities observed in exploitation attempts are tracked as CVE-2026-61979 and CVE-2026-15981 and can be chained together to bypass authentication. Because the miniOrange SAML SSO plugin accepts the signature algorithm from incoming SAML responses instead of enforcing the configured one, an attacker can leverage CVE-2026-61979 to select HMAC-SHA1. This causes the plugin to treat the RSA public key from the identity provider (IdP) as the shared secret.
Cybersecurity company ReliaQuest has confirmed that one of its employees was targeted in a social engineering attack after hackers impersonated a member of the security team. In a statement over the weekend, ReliaQuest said that an attacker called multiple employees and tried to trick them into accessing "a fake ReliaQuest single sign-on (SSO) page behind a content delivery network." Last week, ReliaQuest's Threat Research team shared in a now-deleted post, that the ShinyHunters extortion gang was registering .claims domains to impersonate company's help desks and IT teams. "ReliaQuest is tracking a widespread ShinyHunters campaign using domains that follow the company[.]claims pattern. These domains incorporate the targeted organization’s name or abbreviation under the .claims TLD," read the company's post on X.
A breach at South Korea's government-backed startup platform exposed encrypted personal data after an encryption key was included in an API. Penta Security explains why encryption keys must be securely managed and kept separate from the data they protect.
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)
Red Hat and the Keycloak project have released patches to address a critical security flaw in the open-source identity and access management server that could allow an unauthenticated remote attacker to take over any user account by forcing a password reset. The vulnerability, assigned the CVE identifier CVE-2026-18963, is rated 9.1 on the CVSS scoring system by Red Hat, which acts as
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.
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)
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.
Windows named pipes provide fast interprocess communication, but weak access controls can expose privileged services to untrusted processes. ThreatLocker explains how endpoint verification, command authorization, strict input validation, and narrowly scoped privileges can help secure named-pipe communication.
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