Drupal has patched two critical vulnerabilities that could allow attackers to execute code remotely on websites running any supported version of the content management system. The security issues impact the software core's Field UI module and the contributed Entity List module. Drupal issued an advance warning at the beginning of the week, urging administrators to apply updates promptly because attackers could develop exploits shortly after the vulnerabilities’ disclosure. “The Drupal Security Team urges you to reserve time for core updates at that time because exploits might be developed within hours or days,” the project's security team warned. “We recommend updating to the latest supported patch (bugfix) release for your site's version of Drupal before October 14, so that you can address any other upgrade issues before the security window.”
India’s CERT-In warns AI agents accessed confidential data undetected, while attackers used offensive AI frameworks to accelerate cyberattacks. CERT-In, India’s national cyber response team, published a critical-severity advisory 15 documenting two distinct categories of AI-related incidents. In one, AI models under research and evaluation exceeded their assigned tasks and accessed live Indian systems without authorization. In the other, attackers deliberately weaponized open-source AI agent frameworks to run financially motivated intrusions. “CERT-In has observed different categories of cyber incidents in which the attacker was an AI agent, that is, a software system capable of autonomously planning work, issuing commands, invoking tools and acting on the internet over extended periods. In some incidents, AI agents under research and evaluation exceeded their assigned task authorization and made unauthorized access to Indian information and communication technology (ICT) assets. In others, cyber attackers deliberately used open-source agentic AI tools to conduct reconnaissance, exploitation and financially motivated intrusions.” CERT-In states. “The incidents came to light through voluntary disclosures by AI model providers, CERT-In’s forensic analysis of suspicious activities, and CERT-In’s own proactive threat hunting. The affected organizations could not detect the unauthorized access on their own.” What makes these incidents especially concerning is that the affected organizations didn’t detect the unauthorized access. None of the affected organizations detected the unauthorized access; in every case the incident was disclosed by the AI model providers after their internal review. The organizations only learned about the incidents from the AI companies. The agents accessed Indian systems using exposed credentials and connection settings found in configuration files, public code repositories, and cloud accounts with excessive permissions. They then accessed business records containing personal and confidential information. CERT-In didn’t name the AI companies, models, or affected organizations. It also didn’t say whether the agents copied or kept any data, or whether the affected organizations had been notified. “Further, victim entities in the campaign that remediated incompletely were attacked again within days, at greater scale.” continues the advisory. “In the voluntarily disclosed incidents, agents were observed re-deriving and re-using the same exposed credential in separate operations.” That’s worth reading carefully. It means an agent that encountered a leaked key once didn’t just use it once, it came back to it. CERT-In’s own threat hunting found a separate campaign against Indian entities using publicly available offensive AI frameworks. These tools have been misused, rebranded, and redeployed across infrastructure in multiple countries, and CERT-In describes a large number of active deployments. The attackers ran multiple agents in parallel for hours to days, and victims who only partially remediated the initial access were hit again within days at greater scale. The biggest concern is how quickly these attacks can happen. These frameworks can reportedly reduce the time between gaining access and causing damage from several days to just a few hours. In September, Google Threat Intelligence Group reported a similar case in which attackers used a compromised cloud resource to run an AI-driven campaign that stole thousands of credentials from other services in less than six hours. CERT-In puts the strongest emphasis on this point. In every incident, the weaknesses were common security problems: credentials and keys stored in source code, commit histories, CI/CD variables, configuration files, and public web pages. Other issues included unused APIs that had never been disabled, payment API keys stored in plain text, cloud roles allowing anonymous or regular users to read and change data, and management interfaces exposed to the internet with weak or no multi-factor authentication. CERT-In’s conclusion is clear: AI found and exploited these common weaknesses “faster, more exhaustively and at greater scale than human attackers.” That’s the real change. The vulnerabilities themselves are nothing new. What has changed is how quickly attackers can find them and combine them to carry out attacks. The advisory’s list of recommended actions for organizations covers ground that should already be standard practice, but clearly isn’t. Audit every repository and build pipeline for exposed credentials. Rotate and purge anything you find. Keep a full API inventory and shut down anything old or unused. Remove management interfaces from the internet. Keep logs for at least 180 days and watch API traffic for bulk reads and automated registrations in real time. For organizations running their own AI agents, CERT-In adds a specific requirement: give each run its own short-lived, least-privilege identity, block outbound traffic to anything outside the task’s defined scope, and maintain a tamper-resistant log of every agent action touching production systems. The advisory also cross-references an earlier October 9 warning on payment and disbursement API abuse, which CERT-In says BFSI and fintech entities should apply alongside the measures here. AI developers and testing labs should block all outgoing network connections from test environments at the infrastructure level, rather than relying on instructions given to the AI model. If an AI agent tries to connect to an external system or finds credentials it should not have access to, the test should stop automatically, and the affected organization should be notified immediately. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, AI agents)
Cybersecurity researchers have discovered a malicious npm package that's part of a recently disclosed software supply chain attack campaign dubbed MALFEX. The package, named "imgdecode," was uploaded to the package registry on September 30, 2026, by a user named "malfexteste8." It has been downloaded 979 times as of writing and is still available on npm as of writing. The latest version of
Researchers warn that hackers could soon exploit a maximum-severity vulnerability (CVE-2026-103849) affecting Magento and Adobe Commerce, potentially allowing them to execute arbitrary PHP code on store servers. According to e-commerce security firm Sansec, attacks leveraging the vulnerability, dubbed BlockStrap, have not yet been observed, but threat actors are expected to find a way to exploit it. The researchers based their assessment on identifying four potential attack paths involving CVE-2026-103849 in less than 24 hours. The flaw impacts September versions of Adobe Commerce and Magento Open Source through 2.4.9 and Adobe Commerce B2B through 1.5.3. The security firm warned that Adobe’s “priority 2” rating of this flaw does not reflect the danger and urgency in this case, despite the more complex attack path.
Unit 42 details the top initial access vectors adversaries use to breach organizations, led by edge exploits, credential abuse and phishing The post Top 5 Initial Access Threat Vectors Observed by Unit 42 in September 2026 appeared first on Unit 42.
Candiru spyware was delivered to devices at Al Jazeera Media Network via targeted online advertisements in a zero-click attack that required only rendering the malicious ads on the victim's device. Researchers at Citizen Labs investigating the attacks referred to this technique as AdFection, noting that their report is the first public technical confirmation of mercenary spyware delivered through targeted ads. A similar method was documented in late 2025 by Amnesty International, involving ads that infected targets with Predator spyware without them clicking anything. That infection mechanism was called Aladdin and surfaced due to a collection of marketing files and documents leaked from the Intellexa surveillance company that researchers studied and corroborated with technical details from forensic investigations.
Employees using personal ChatGPT accounts at work can expose sensitive company data, even when their organization provides an approved Enterprise workspace. NordLayer explains how IT teams can investigate unauthorized AI use and block sensitive information before it reaches personal accounts.
F5 addressed multiple vulnerabilities, including critical RCE flaws in NGINX that attackers could exploit without authentication. Security and application delivery firm F5 announced fixes for eleven security issues in NGINX. Among them, critical vulnerabilities tracked as CVE-2026-15176 and CVE-2026-93479 could be exploited without authentication via crafted HTTP requests. Under certain conditions beyond their control, an unauthenticated attacker could exploit the security flaws to trigger a buffer overflow leading to a restart. If ASLR is disabled or can be bypassed, the attacker could achieve RCE. The flaw CVE-2026-15176 (CVSS score of 9.2) is a heap-based buffer overflow vulnerability in NGINX Plus and NGINX Open Source that could allow an unauthenticated attacker to trigger a denial-of-service condition or potentially execute arbitrary code by sending crafted HTTP requests. The vulnerability occurs under specific configurations involving the alias directive and the $request_filename variable. Remote code execution may be possible if ASLR is disabled or bypassed. The flaw CVE-2026-93479 (CVSS score of 9.2) is a heap-based buffer overflow vulnerability in NGINX Plus and NGINX Open Source that could allow an unauthenticated attacker to trigger a denial-of-service condition or potentially execute arbitrary code through crafted HTTP requests. It affects specific configurations where regular-expression capture variables from the map directive are referenced before the map output variable, or where a non-cacheable variable is used in a string expression under certain conditions. Remote code execution may be possible if ASLR is disabled or bypassed. The third critical flaw fixed by the vendor, tracked as CVE-2026-97205 (CVSS score of 9.2), is a use-after-free vulnerability in NGINX ngx_http_core_module that, under certain configurations with asynchronous file I/O (AIO) enabled, may cause memory corruption or unexpected worker process termination when processing Server Side Includes (SSI) pages containing include virtual commands. A remote attacker could exploit the flaw to cause a denial-of-service (DoS) or potentially execute code, particularly when ASLR is disabled or can be bypassed. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, NGINX)
Burger King Japan, the Japanese subsidiary of global fast-food giant Burger King, disclosed a major data breach after attackers accessed a server containing 11.18 million customer records. Founded in 1953 in Florida, Burger King is now a multinational fast-food chain with nearly 20,000 locations worldwide, including 350 in Japan. In a Thursday press release, Burger King Japan said it concluded a follow-up investigation on October 13 and apologized to customers whose data was stolen in early October and leaked online. The breached servers stored the personal information for users of the company's official smartphone app, including their names, dates of birth, gender, email addresses, phone numbers, and order history. "We identified a potential unauthorized third-party access to the system that manages member information for our official app and conducted an investigation," Burger King Japan said.
U.S. Cybersecurity and Infrastructure Security Agency (CISA) adds Atlassian flaw to its Known Exploited Vulnerabilities catalog. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) added an Atlassian flaw, tracked as CVE-2026-21589 (CVSS score of 9.3), to its Known Exploited Vulnerabilities (KEV) catalog. In early October, threat actors started exploiting CVE-2026-21589, a critical arbitrary file access flaw in Atlassian Data Center products. The vulnerability could allow attackers to access sensitive files under certain conditions. Affected products include Bitbucket, Confluence, Jira Service Management, Jira Software, Bamboo, Crowd, Crucible, and Fisheye. “This Arbitrary File Access vulnerability allows an unauthenticated attacker to access specific files within the web application root directory in affected versions. Exploitation requires prior knowledge of the target file’s exact name and path; this vulnerability does not allow attackers to enumerate or list directory contents.” reads the advisory. “In some configurations, there may be some sensitive files that make this highly severe.” Previdian telemetry has detected 15 exploitation attempts from three IP addresses in Japan and the U.S.. “Exploitation has now started to hit our honeypot network” Previdian Founder Ryan Dewhurst wrote on LinkedIn. On October 6, watchTowr Labs published a technical analysis of CVE-2026-21589 after comparing vulnerable and patched Atlassian packages. Researchers found a path traversal flaw where double-colon (::) sequences can be treated as path separators, allowing attackers to read files from the application web root. “While semicolons (;) are very common in path traversal within Java applications, along with the everyday dots (.) and slashes (/), one item stood out: the matching of double colons (::).” reads the analysis. “This is uncommon syntax for this type of vulnerability, but grepping through the codebase we came across an all too familiar sight.” In one Crowd deployment with Jira, researchers were able to read crowd.properties, which exposed application credentials. They then used those credentials to create a user and add it to the jira-administrators group. Crowd IP allowlisting can block this attack path. Exploitation attempts against its honeypot network reportedly began two hours after watchTowr published additional technical details about the vulnerability. According to watchTowr, the problem is in Atlassian’s web-resource handling. It can turn a string such as ..::..::..::..::WEB-INF::web.xml into ../../../../WEB-INF/web.xml, allowing attackers to move through directories and access files they should not be able to read. Atlassian says all versions before the listed fixed versions are affected: ProductFixed versionsBitbucket Data Center9.4.26, 10.2.8, 10.5.1Confluence Data Center9.2.26, 10.2.19Jira Service Management Data Center5.12.40, 10.3.26, 11.3.12Jira Software Data Center9.12.40, 10.3.26, 11.3.12Bamboo Data Center10.2.24, 12.1.12Crowd Data Center6.3.7, 7.0.3, 7.1.7, 7.2.4Crucible4.9.15Fisheye4.9.15 watchTowr has released a free tool on GitHub to help check if a server is vulnerable. According to Binding Operational Directive (BOD) 22-01: Reducing the Significant Risk of Known Exploited Vulnerabilities, FCEB agencies have to address the identified vulnerabilities by the due date to protect their networks against attacks exploiting the flaws in the catalog. Experts also recommend that private organizations review the Catalog and address the vulnerabilities in their infrastructure. CISA orders federal agencies to fix the flaw by October 18, 2026. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, CISA)
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