Making secret scanning more trustworthy: Reducing false positives at scale

Secret scanning plays a critical role in protecting developers and organizations. It helps catch exposed credentials early and prevents small mistakes from turning into real incidents. At GitHub's scale, even small inefficiencies create real friction. Too many false positives make alerts harder t...

AI Security at Machine Speed: A Roadmap for Modern AppSec

With AI API calls set to grow 1,000x by 2027, you need a roadmap to secure your enterprise against agentic threats...

Assessing Automated Prompt Injection Attacks in Agentic Environments

Indirect prompt injection poses a critical threat to LLM agents that interact with untrusted external data, yet automated attack methods--proven effective for jailbreaking--remain underexplored in realistic agentic settings. We present a comprehensive empirical evaluation of automated prompt...

State of Agentic AI Security and Governance

An OWASP white paper analyzing the security, governance, and risk management considerations surrounding agentic AI systems, including autonomous decision-making, tool access, prompt injection, data protection, and organizational oversight. This is version 2.01...

CVE-2026-44246

nnU-Net is a semantic segmentation framework that automatically adapts its pipeline to a dataset. Prior to 2.4.1, the nnU-Net Issue Triage workflow in .github/workflows/issue-triage.yml is vulnerable to Agentic Workflow Injection. The workflow sets allowednonwriteusers: $...

Updating the taxonomy of failure modes in agentic AI systems: What a year of red teaming taught us

In this article 1. Why the Taxonomy Needed Updating 2. Seven new failure modes 3. Operational findings: What red teaming showed 4. New mitigations 5. What to do this quarter When the Microsoft AI Red Team published the Taxonomy of Failure Modes in Agentic AI Systems in April 2025, the goal was a...

Updating the taxonomy of failure modes in agentic AI systems: What a year of red teaming taught us

In this article 1. Why the Taxonomy Needed Updating 2. Seven new failure modes 3. Operational findings: What red teaming showed 4. New mitigations 5. What to do this quarter When the Microsoft AI Red Team published the Taxonomy of Failure Modes in Agentic AI Systems in April 2025, the goal was a...

Agentic AI Is Transforming Defense, But Only Secure IT Infrastructure Will Maximize It

Over the past several weeks, the cybersecurity community has been reminded how quickly frontier and agentic AI in defense networks can challenge our assumptions. When Anthropic's Claude Mythos model was made available to a limited set of organizations as a technical preview, it was reported that ...

ate (>=0.1.0 <=0.8.0), ate-auth (>=1.1.0 <=1.6.0) +73 more potentially affected by unknown CVE via pqcrypto-traits (>=0.1.1 <=0.3.5)

pqcrypto-traits CARGO version =0.1.1, =0.1.0, =1.1.0, =1.0.0, =1.1.0, =2.0.0, =0.1.2-alpha, =0.1.4, =0.1.1, =0.1.0, =0.1.1, =0.1.0, =0.1.2 - envencryptiontool =0.9.17 - ever-crypto =0.1.0 - hanzo-agentic =1.1.21 and more Source cves: unknown CVE Source advisory: OSV:RUSTSEC-2026-0162...

Shrinking the IAM Attack Surface through Identity Visibility and Intelligence Platforms (IVIP)

The Fragmented State of Modern Enterprise Identity Enterprise IAM is approaching a breaking point. As organizations scale, identity becomes increasingly fragmented across thousands of applications, decentralized teams, machine identities, and autonomous systems. The result is Identity Dark Matter...

@byside/llm (>=0.1.0 <=0.1.1), agentic-control (=1.1.0) potentially affected by unknown CVE via ai-sdk-ollama (=1.1.0)

ai-sdk-ollama NPM version =1.1.0 is affected by a known vulnerability. The following packages have a transitive dependency on ai-sdk-ollama and may be impacted: - @byside/llm =0.1.0, =0.1.1 - agentic-control =1.1.0 Source cves: unknown CVE Source advisory: SNYK:JS-AISDKOLLAMA-17146454...

PT-2026-48122

Name of the Vulnerable Software and Affected Versions @agenticmail/mcp versions prior to 0.9.27 Description When started with the --http flag or the MCP HTTP=1 variable, the software exposes a Streamable HTTP transport. In this mode, the '/mcp' endpoint accepts requests without an HTTP...

Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems

Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supply-chain risk: malicious contributors can hide harmful behavior inside skills that appear benign under superficial inspection. However, existing...

Investigating Detection and Obfuscation of Prompt Injection Attacks against Software Reverse Engineering AI Agents

Agentic software reverse engineering systems are vulnerable to prompt injection attacks placed into the source code of executable binary files. This research demonstrates defensive tactics for detecting the presences of prompt injection strings in the decompiler output of adversarial example...

OWASP FinBot CTF 0.2

FinBot is an Agentic AI security CTF platform from OWASP. Interact with AI agents, exploit real vulnerabilities, and learn to secure agentic systems. All from your browser...

The Alert Firehose Finally Meets Its Match

Ask a cybersecurity pro about Network Detection and Response NDR and you might still hear "Noisy," "Too much data." But ask the teams running NDR that includes agentic AI capabilities and you'll hear they're actually using it to catch threats earlier, triage faster, and chase fewer false positive...

Introducing RAMPART and Clarity: Open source tools to bring safety into Agent development workflow

In this article 1. Why we are investing in this 2. RAMPART: Continuous safety testing for agentic AI 3. Clarity: Helping check software engineering assumptions 4. RAMPART and Clarity available now The AI systems shipping inside enterprises today are fundamentally different from the ones we were...

Detecting Offensive Cyber Agents: A Detection-In-Depth Approach

Artificial Intelligence AI agents can now orchestrate cyberattacks. This development is already increasing the speed and scale of cyber attacks, decreasing attack costs, and improving the operational autonomy of cyber capabilities. To defend against these emerging threats, actors must first devel...

Agentic Governance: Why It Matters Now

AI agents now act inside the trust boundary with real credentials, and agentic governance is what keeps them from quietly breaking things at machine speed...

ADR: An Agentic Detection System for Enterprise Agentic AI Security

We present the Agentic AI Detection and Response ADR system, the first large-scale, production-proven enterprise framework for securing AI agents operating through the Model Context Protocol MCP. We identify three persistent challenges in this domain: 1 limited observability -- existing Endpoint...