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127 articles published

April 15, 2026

OpenAI Launches GPT-5.4-Cyber with Expanded Access for Security Teams

ATLAS OWASP HIGH ▲ 7.2 The Hacker News Apr 15, 2026

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.

AML.T0054 - LLM Jailbreak AML.T0051 - LLM Prompt Injection AML.T0047 - ML-Enabled Product or Service AML.T0040 - ML Model Inference API Access AML.T0031 - Erode ML Model Integrity

AI-Driven Pushpaganda Scam Exploits Google Discover to Spread Scareware and Ad Fraud

ATLAS OWASP HIGH ▲ 6.2 The Hacker News Apr 15, 2026

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.

AML.T0047 - ML-Enabled Product or Service AML.T0043 - Craft Adversarial Data AML.T0019 - Publish Poisoned Datasets

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

ATLAS OWASP HIGH ▲ 7.8 SANS Internet Storm Center Apr 15, 2026

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.

AML.T0012 - Valid Accounts AML.T0040 - ML Model Inference API Access AML.T0044 - Full ML Model Access AML.T0010 - ML Supply Chain Compromise

April 14, 2026

How Hackers Are Thinking About AI

ATLAS OWASP MEDIUM ▲ 6.2 Schneier on Security Apr 14, 2026

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.

AML.T0047 - ML-Enabled Product or Service AML.T0054 - LLM Jailbreak AML.T0051 - LLM Prompt Injection AML.T0043 - Craft Adversarial Data

Your MTTD Looks Great. Your Post-Alert Gap Doesn't

ATLAS OWASP HIGH ▲ 7.2 The Hacker News Apr 14, 2026

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.

AML.T0047 - ML-Enabled Product or Service AML.T0040 - ML Model Inference API Access AML.T0044 - Full ML Model Access

CSA: CISOs Should Prepare for Post-Mythos Exploit Storm

ATLAS OWASP HIGH ▲ 7.2 Dark Reading Apr 14, 2026

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.

AML.T0051 - LLM Prompt Injection AML.T0054 - LLM Jailbreak AML.T0056 - LLM Meta Prompt Extraction AML.T0057 - LLM Data Leakage AML.T0047 - ML-Enabled Product or Service AML.T0040 - ML Model Inference API Access

OWASP GenAI Security Project Gets Update, New Tools Matrix

ATLAS OWASP MEDIUM ▲ 7.2 Dark Reading Apr 14, 2026

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.

AML.T0051 - LLM Prompt Injection AML.T0054 - LLM Jailbreak AML.T0057 - LLM Data Leakage AML.T0047 - ML-Enabled Product or Service AML.T0056 - LLM Meta Prompt Extraction AML.T0010 - ML Supply Chain Compromise

OpenAI Impacted by North Korea-Linked Axios Supply Chain Hack

ATLAS OWASP HIGH ▲ 7.5 SecurityWeek Apr 14, 2026

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.

AML.T0010 - ML Supply Chain Compromise AML.T0047 - ML-Enabled Product or Service

April 13, 2026

Python Supply-Chain Compromise

ATLAS OWASP HIGH ▲ 8.2 Schneier on Security Apr 13, 2026

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.

AML.T0010 - ML Supply Chain Compromise AML.T0018 - Backdoor ML Model AML.T0047 - ML-Enabled Product or Service

Over 1,000 Exposed ComfyUI Instances Targeted in Cryptomining Botnet Campaign

ATLAS OWASP HIGH ▲ 7.2 The Hacker News Apr 13, 2026

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.

AML.T0010 - ML Supply Chain Compromise AML.T0047 - ML-Enabled Product or Service AML.T0040 - ML Model Inference API Access

Google's Vertex AI Is Over-Privileged. That's a Problem

ATLAS OWASP HIGH ▲ 8.5 Dark Reading Apr 13, 2026

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.

AML.T0051 - LLM Prompt Injection AML.T0057 - LLM Data Leakage AML.T0040 - ML Model Inference API Access AML.T0047 - ML-Enabled Product or Service AML.T0012 - Valid Accounts

Flowise AI Agent Builder Under Active CVSS 10.0 RCE Exploitation; 12,000+ Instances Exposed

ATLAS OWASP CRITICAL ▲ 9.4 The Hacker News Apr 13, 2026

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.

AML.T0047 - ML-Enabled Product or Service AML.T0040 - ML Model Inference API Access AML.T0010 - ML Supply Chain Compromise

April 11, 2026

How We Broke Top AI Agent Benchmarks: And What Comes Next

ATLAS OWASP CRITICAL ▲ 9.2 HN AI Security Apr 11, 2026

Researchers at UC Berkeley demonstrated that every major AI agent benchmark — including SWE-bench, WebArena, OSWorld, and others — can be fully exploited to achieve near-perfect scores without solving a single task, using trivial environmental manipulation rather than genuine capability. The attacks include pytest hook injection, config file leakage, DOM manipulation, and reward component bypassing, with zero LLM calls required in most cases. This represents a systemic integrity failure in the evaluation infrastructure underpinning AI deployment decisions across industry and research.

AML.T0043 - Craft Adversarial Data AML.T0031 - Erode ML Model Integrity AML.T0047 - ML-Enabled Product or Service AML.T0051 - LLM Prompt Injection AML.T0015 - Evade ML Model

Anthropic Claude Mythos Preview: The More Capable AI Becomes, the More Security It Needs

ATLAS OWASP LOW ▲ 6.2 CrowdStrike Blog Apr 11, 2026

CrowdStrike, as a founding member of Anthropic's Mythos program, is highlighting the security challenges posed by increasingly capable frontier AI models, signaling a growing industry focus on securing agentic and large-scale AI systems. The article underscores the philosophical and practical position that AI capability gains must be matched by proportional security investment. While the piece is primarily a vendor partnership announcement and executive viewpoint, it reflects an important industry trend toward formalising AI-specific security frameworks and tooling.

AML.T0047 - ML-Enabled Product or Service AML.T0051 - LLM Prompt Injection AML.T0040 - ML Model Inference API Access

April 10, 2026

US summons bank bosses over cyber risks from Anthropic's latest AI model

ATLAS OWASP CRITICAL ▲ 8.5 HN AI Security Apr 10, 2026

The US Treasury convened major bank executives to discuss cybersecurity risks posed by Anthropic's unreleased Claude Mythos model, which the company claims has surpassed nearly all human experts at finding and exploiting software vulnerabilities. A code leak prompted Anthropic to publicly acknowledge the model's unprecedented offensive cyber capability, raising systemic financial sector risk concerns. The meeting signals growing regulatory awareness of AI-enabled cyber threats to critical financial infrastructure.

AML.T0047 - ML-Enabled Product or Service AML.T0044 - Full ML Model Access AML.T0040 - ML Model Inference API Access AML.T0010 - ML Supply Chain Compromise

Framework Coverage

ATLAS

MITRE ATLAS 58 mapped techniques

OWASP

OWASP LLM Top 10 41 mapped techniques

AI Security News. Framework Analysis.Structural Insight.