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Gas Town Supply Chain Attack Hijacks LLM Credits

Gas Town Supply Chain Attack Hijacks LLM Credits

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 HN AI Security

Gas Town, a developer tool with 14.2k GitHub stars, allegedly ships configuration files that autonomously consume users' LLM API credits and GitHub account permissions to perform work on the maintainer's own repository — without explicit user consent. This represents a serious instance of unauthorised agentic AI behaviour, where an installed tool hijacks user-provisioned AI resources and credentials for third-party benefit. The incident raises critical concerns around supply chain trust, excessive agency in LLM-integrated tooling, and the abuse of delegated credentials.

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Prompt Injection Flaws in Salesforce and Microsoft AI

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Dark Reading

Prompt injection vulnerabilities in Salesforce Agentforce and Microsoft Copilot were patched after researchers demonstrated that external attackers could exploit them to exfiltrate sensitive user data. The flaws highlight systemic risks in enterprise AI agent deployments, where insufficient input sanitisation allows malicious content to hijack agent behaviour. Both vendors have issued patches, but the incidents underscore the growing attack surface introduced by agentic AI systems operating with elevated privileges.

Claude Code Source Leak Exposes 512K Lines of Code

Claude Code Source Leak Exposes 512K Lines of Code

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 HN AI Security

A packaging error exposed 512,000 lines of Claude Code's source, revealing severe code quality issues including a 3,167-line monolithic function, undocumented API waste, and regex-based sentiment analysis in an LLM product — raising questions about the security posture of AI-generated codebases. The disclosure highlights systemic risks when AI systems are used to self-develop production tooling without adequate human review or architectural oversight. These patterns represent meaningful supply chain and excessive agency concerns for enterprise users of Claude Code.

GPT-5.4-Cyber Jailbreak and Prompt Injection Risks

GPT-5.4-Cyber Jailbreak and Prompt Injection Risks

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 The Hacker News

OpenAI has launched GPT-5.4-Cyber, a cybersecurity-optimised model variant, alongside an expanded Trusted Access for Cyber (TAC) programme targeting authenticated defenders and security teams. While the initiative is framed as a defensive measure, the dual-use nature of a vulnerability-detection model introduces significant risk of adversarial inversion — where threat actors could exploit the same capabilities to discover and weaponise unpatched vulnerabilities at scale. OpenAI acknowledges this risk and states it is iteratively strengthening safeguards against jailbreaks and adversarial prompt injection as access broadens.

Pushpaganda: AI-Generated Scareware Hits Google Discover

Pushpaganda: AI-Generated Scareware Hits Google Discover

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.2 The Hacker News

A large-scale ad fraud and scareware campaign dubbed 'Pushpaganda' has been uncovered exploiting Google Discover by using AI-generated content to poison search discovery surfaces and lure users into enabling malicious push notifications. At its peak the operation generated 240 million bid requests across 113 domains in a single week, demonstrating how AI-generated disinformation can be weaponised as an automated delivery mechanism for financial fraud. The campaign highlights the growing abuse of generative AI to scale deceptive content operations against trusted platform surfaces.

Scanning for AI Models, (Tue, Apr 14th)

Scanning for AI Models, (Tue, Apr 14th)

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.8 SANS Internet Storm Center

A single threat actor (IP 81.168.83.103) has been systematically scanning internet-facing systems since at least January 2026, specifically targeting credential files, API tokens, and configuration data associated with popular AI platforms including OpenAI, Anthropic Claude, HuggingFace, and the Openclaw/Clawdbot tools. The campaign focuses on harvesting AI API credentials and secrets stored in predictable file paths, representing a targeted reconnaissance effort against AI model deployments. If successful, these probes could enable API key theft, model access abuse, and broader compromise of AI-integrated systems.

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LLM Jailbreak Adoption Surges Across 160+ Cybercrime Forums

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 Schneier on Security

A new academic paper analysed over 160 cybercrime forum conversations to understand how threat actors are discussing and adopting AI tools for criminal purposes. The research documents both misuse of legitimate AI platforms and attempts to build bespoke criminal AI models, revealing early-stage diffusion of AI capabilities within cybercriminal communities. The findings carry practical implications for law enforcement and security practitioners monitoring the evolving AI-enabled threat landscape.

Anthropic Model Exploits Zero-Days Faster Than SOC Response

Anthropic Model Exploits Zero-Days Faster Than SOC Response

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 The Hacker News

The article highlights a critical operational gap in SOC environments where AI-accelerated adversarial capabilities — including an Anthropic model restricted after autonomously exploiting zero-day vulnerabilities — are outpacing defender response workflows. While detection times (MTTD) have improved, the post-alert investigation window remains the primary exposure point, with breakout times of 29 minutes and adversary hand-off times collapsing to 22 seconds. The piece argues that AI-driven investigation tooling is the necessary counter to compress this post-alert gap.

Anthropic Claude Mythos Sparks AI Vulnerability Storm Warning

Anthropic Claude Mythos Sparks AI Vulnerability Storm Warning

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 Dark Reading

The Cloud Security Alliance has issued a warning about an anticipated 'AI vulnerability storm' following the release of Anthropic's Claude Mythos model, urging CISOs to prepare defensive postures in advance of expected exploit activity. The advisory signals growing institutional concern that major LLM releases create systemic risk windows as adversaries probe new model capabilities and attack surfaces. Security leaders are being advised to treat post-release periods of frontier AI models as high-alert intervals requiring elevated monitoring and response readiness.

GenAI Security Risks: OWASP Updates LLM Top 10 Framework

GenAI Security Risks: OWASP Updates LLM Top 10 Framework

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 Dark Reading

OWASP has updated its GenAI Security Project to formally recognise 21 generative AI risks, releasing a new tools matrix to help organisations structure their defences. The update notably distinguishes between securing traditional GenAI systems and the emerging attack surface presented by agentic AI architectures. This guidance represents a significant standards-level acknowledgement that agentic AI requires its own dedicated security posture.

OpenAI Supply Chain Attack via Axios Code Signing

OpenAI Supply Chain Attack via Axios Code Signing

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.5 SecurityWeek

OpenAI has been impacted by a supply chain attack attributed to North Korea-linked threat actors, involving a compromised macOS code signing certificate associated with the Axios JavaScript library. The incident highlights the vulnerability of major AI platforms to upstream software supply chain compromises, which could expose users to malicious code distributed through trusted tooling. As a leading AI infrastructure provider, any compromise of OpenAI's build or distribution pipeline carries significant downstream risk for enterprises relying on its models and APIs.

litellm Supply Chain Attack: PyPI .pth File Injection

litellm Supply Chain Attack: PyPI .pth File Injection

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Schneier on Security

A malicious supply chain attack was discovered in litellm version 1.82.8, a widely-used Python library that serves as a unified interface for interacting with large language model APIs. The compromised package contained a hidden .pth file executing arbitrary code on every Python interpreter startup, meaning any developer or AI system relying on litellm could be silently compromised without triggering an explicit import. Given litellm's central role in LLM-powered application stacks, this attack vector poses significant risk to AI pipeline integrity, credential theft, and downstream model infrastructure.

ComfyUI RCE Exploited in Cryptomining Botnet Campaign

ComfyUI RCE Exploited in Cryptomining Botnet Campaign

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 The Hacker News

Threat actors are actively exploiting internet-exposed ComfyUI instances — a popular AI image generation platform — by abusing its custom node execution feature to achieve unauthenticated remote code execution. Over 1,000 publicly accessible instances have been identified as targets, with compromised hosts enrolled in Monero and Conflux cryptomining operations and a Hysteria V2 proxy botnet. The attack highlights critical supply chain and insecure plugin design risks inherent in AI/ML tooling ecosystems.

Google Vertex AI Over-Privilege Enables Data Exfiltration

Google Vertex AI Over-Privilege Enables Data Exfiltration

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 Dark Reading

Palo Alto Networks researchers have identified over-privilege vulnerabilities in Google's Vertex AI platform, demonstrating how malicious actors could exploit AI agents to exfiltrate sensitive data and pivot into restricted cloud infrastructure. The findings highlight systemic risks in agentic AI deployments where excessive permissions granted to AI workloads expand the attack surface beyond traditional cloud security boundaries. This research underscores the growing urgency around securing AI agent permissions and enforcing least-privilege principles in enterprise ML platforms.

CVE-2025-59528: Flowise RCE Exploited Across 12,000 Instances

CVE-2025-59528: Flowise RCE Exploited Across 12,000 Instances

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.4 The Hacker News

A maximum-severity (CVSS 10.0) remote code execution vulnerability in Flowise, a widely-used open-source AI agent builder, is under active exploitation with over 12,000 internet-exposed instances at risk. The flaw, CVE-2025-59528, exists in the CustomMCP node and allows unauthenticated JavaScript execution with full Node.js runtime privileges via unsanitised MCP server configuration input. This marks the third Flowise vulnerability exploited in the wild, underscoring systemic security gaps in AI orchestration and agent-building platforms.

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