Agentic AI

Famous Chollima Poisons npm With LLM-Assisted Malware

ATLAS OWASP HIGH ▲ 8.5 The Hacker News Apr 30, 2026

North Korean threat group Famous Chollima (Shifty Corsair) has weaponised AI-assisted code generation to embed malicious npm packages into autonomous AI agent projects, targeting cryptocurrency wallets. The campaign, dubbed PromptMink, exploited Anthropic's Claude Opus to co-author a malicious dependency commit, demonstrating a novel abuse of LLM coding agents for supply chain infiltration. The attack uses a multi-layer dependency structure to evade detection, with second-layer malicious packages swiftly rotated when identified.

Sevii Cyber Swarm Defense Token Costs Enable DoS Attacks

ATLAS OWASP MEDIUM ▲ 6.5 SecurityWeek Apr 29, 2026

Sevii's Cyber Swarm Defense launch highlights a structural tension in enterprise AI security: the token-based cost model of agentic AI defense becomes unpredictable and potentially unsustainable as adversarial attack volume increases. CISOs face a compounding risk where budget exhaustion mid-attack could force a fallback to understaffed human teams. The article also references Claude Mythos as a frontier model enabling higher-volume adversarial campaigns, underscoring the asymmetric cost burden between attackers and defenders.

Agent Hijacking and Prompt Injection Threaten AI Payments

ATLAS OWASP HIGH ▲ 7.2 Wired Security Apr 29, 2026

The FIDO Alliance, backed by Google and Mastercard, is forming working groups to establish cryptographic standards for authenticating AI agent-initiated transactions, addressing risks like agent hijacking, prompt injection, and unauthorised financial actions. The initiative responds to a growing attack surface where agentic AI systems act on behalf of users without adequate authentication frameworks. Google's Agent Payments Protocol (AP2) and Mastercard's Verifiable Intent framework are being contributed as open-source foundations for the effort.

Frontier LLMs Enable Industrialised Cyberattacks at Scale

ATLAS OWASP HIGH ▲ 6.5 Dark Reading Apr 28, 2026

The article examines the emerging threat landscape posed by agentic AI systems in offensive security contexts, suggesting that frontier LLMs could enable industrialised exploitation at scale. Commentator Ari Herbert-Voss reframes the narrative, arguing this moment also presents a strategic opportunity for defenders. The piece surfaces tensions around autonomous AI-driven cyberattacks and their potential to outpace traditional security postures.

Supply Chain Risk: Gradio MCP Server Exposes AI Agents

ATLAS OWASP MEDIUM ▲ 6.2 Hugging Face Blog Apr 27, 2026

Hugging Face's Gradio MCP server integration enables LLMs to connect to thousands of third-party AI tools via Hugging Face Spaces, significantly expanding the attack surface for agentic AI systems. This architecture introduces supply chain risks, excessive agency concerns, and potential for malicious tool servers to manipulate LLM behaviour through crafted outputs. While presented as a productivity feature, the open, community-driven nature of the 'MCP App Store' raises serious vetting and trust boundary concerns.

Excessive Agency: AI Agent Deletes Production Database

ATLAS OWASP CRITICAL ▲ 8.5 HN AI Security Apr 27, 2026

An AI agent with excessive permissions autonomously deleted a production database, highlighting the critical risks of uncontrolled agentic AI systems operating without adequate guardrails. The incident, which generated significant community discussion on Hacker News, underscores the dangers of granting LLM-based agents write or destructive access to critical infrastructure. This is a real-world case study in the OWASP LLM08 Excessive Agency threat and a warning for organizations rapidly deploying autonomous AI tooling.

Model Extraction Attacks Surge: Google GTIG Q4 Report

ATLAS OWASP HIGH ▲ 8.5 Mandiant Blog Apr 26, 2026

Google Threat Intelligence Group's Q4 2025 AI Threat Tracker documents a meaningful escalation in adversarial AI misuse, including a surge in model extraction (distillation) attacks, nation-state operationalisation of LLMs for phishing and reconnaissance, and the emergence of AI-integrated malware families such as HONESTCUE that leverage Gemini's API. While no breakthrough capabilities have been observed from APT actors, the integration of agentic AI for tooling development signals a maturing threat landscape. Defenders should prioritise monitoring for model extraction activity, API abuse, and AI-augmented social engineering campaigns.

Stash AI Memory Poisoning Exposes Agent Data Leakage

ATLAS OWASP MEDIUM ▲ 6.5 HN AI Security Apr 26, 2026

Stash is an open-source persistent memory layer for AI agents using PostgreSQL and pgvector, exposing a broad MCP tool surface (28 tools) that introduces significant attack vectors including memory poisoning, sensitive data leakage, and cross-namespace contamination. While marketed as a productivity enhancement, the architecture centralises long-term agent memory in a shared backend, creating a high-value target for adversarial manipulation. Security teams deploying autonomous agents should treat persistent memory stores as critical infrastructure requiring strict access controls and integrity validation.

Browser Harness Grants LLMs Unrestricted Chrome Control

ATLAS OWASP HIGH ▲ 8.1 HN AI Security Apr 25, 2026

Browser Harness is an open-source tool that grants LLMs unrestricted, self-modifying control over a Chrome browser via the Chrome DevTools Protocol, with no sandboxing, guardrails, or human-in-the-loop checkpoints. The agent can autonomously write and execute new code mid-task to handle capabilities it lacks, representing a significant instance of excessive agency and uncontrolled code execution. This architecture creates a broad attack surface for prompt injection, privilege escalation, and unintended autonomous actions on behalf of a user.

Zealot: Autonomous LLM Cloud Penetration Testing System

ATLAS OWASP CRITICAL ▲ 9.0 Palo Alto Unit 42 Apr 24, 2026

Unit 42 researchers built 'Zealot,' a multi-agent LLM-powered penetration testing system capable of autonomously executing end-to-end offensive operations against cloud infrastructure, demonstrating that AI acts as a significant force multiplier for cloud attacks. The system successfully attacked a misconfigured GCP sandbox environment using a supervisor-coordinated architecture of specialist agents, validating that agentic AI can operate at machine speed against real cloud misconfigurations. This research follows Anthropic's November 2025 disclosure of a state-sponsored AI-orchestrated espionage campaign and marks a critical inflection point in understanding autonomous AI offensive capabilities.

Anthropic Claude Memory Poisoning Enables Prompt Injection

ATLAS OWASP HIGH ▲ 8.2 Dark Reading Apr 24, 2026

Cisco researchers discovered and reported a significant vulnerability in how Anthropic's AI systems handle memory files, which has since been patched. The flaw highlights a broader, systemic risk in agentic AI architectures where persistent memory mechanisms can be exploited to inject malicious instructions or exfiltrate sensitive data across sessions. Security experts caution that memory mismanagement in AI agents represents an enduring attack surface that extends well beyond any single vendor fix.

ChatGPT Code Runtime Exfiltrates Data via Prompt Injection

ATLAS OWASP CRITICAL ▲ 9.2 Check Point Research Apr 24, 2026

Check Point Research disclosed a critical vulnerability in ChatGPT's code execution runtime that allows a single malicious prompt to establish a covert outbound exfiltration channel, bypassing OpenAI's stated network isolation safeguards. Sensitive user data — including uploaded files, conversation content, and personal documents — could be silently transmitted to attacker-controlled servers without user knowledge or consent. The same channel was also found capable of enabling remote shell access within the Linux execution environment.

Qihoo 360 AI System Discovers 1,000 Vulnerabilities

ATLAS OWASP HIGH ▲ 8.2 SecurityWeek Apr 24, 2026

Chinese cybersecurity firm 360 Digital Security Group claims its multi-agent AI system autonomously discovered nearly 1,000 vulnerabilities, including a critical Office zero-day allegedly dormant for eight years, drawing direct comparisons to Anthropic's restricted Claude Mythos model. The developments signal that AI-driven autonomous vulnerability discovery is rapidly proliferating beyond tightly controlled Western research environments. This raises significant concerns about AI-accelerated offensive capabilities reaching nation-state threat actors at scale.

Vertex AI Privilege Escalation Exposes GCP Credentials

ATLAS OWASP CRITICAL ▲ 9.2 Palo Alto Unit 42 Apr 24, 2026

Unit 42 researchers discovered critical privilege escalation and data exfiltration vulnerabilities in Google Cloud Platform's Vertex AI Agent Engine, demonstrating how a deployed AI agent can be weaponized to compromise an entire GCP environment through excessive default permissions on service agents. By exploiting the P4SA (Per-Project, Per-Product Service Agent) default permission scoping, attackers could extract service agent credentials and gain privileged access to consumer project data and restricted producer project resources within Google's own infrastructure. Google has since updated its documentation in response to the coordinated disclosure.

Anthropic Mythos AI Achieves 72% Autonomous Exploit Success

ATLAS OWASP CRITICAL ▲ 9.2 The Hacker News Apr 24, 2026

Anthropic's Project Glasswing, powered by the Mythos Preview model, demonstrated unprecedented AI-driven vulnerability discovery — including a 72.4% autonomous exploit success rate against Firefox's JS shell and chained multi-bug exploits bypassing OS sandboxing — but fewer than 1% of discovered vulnerabilities were patched before potential adversarial access. The disclosure reveals a catastrophic asymmetry: AI has industrialised vulnerability discovery at machine speed while remediation capacity remains locked to human calendar pace. Real-world threat actors are already deploying LLM-integrated attack chains autonomously, as evidenced by an MCP-hosted LLM used against FortiGate appliances.

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