In this roundup the 1-SEC threat intelligence team walks through the May 3 intelligence cycle—253 reviewed items spanning CISA KEV, NVD, the Go Vulnerability Database, and ten editorial feeds—along with NATS dependency hardening and new AI Containment checks for hostile tool payloads, all without expanding the runtime dependency footprint.
The April 23 threat cycle pushed hard on revoked-token reuse, trusted webhook abuse, dangerous AI-generated defaults, poisoned model artifacts, and parser-level file exploits. Here is what shifted in the threat landscape and what 1-SEC now covers by default.
Weekly threat intelligence reports and release notes are temporarily paused while 1-SEC is under active evaluation across multiple hackathons. Development continues — public updates resume after judging wraps.
We took the detection knowledge from 1-SEC's 16 modules and built it into a GitLab Duo agent. SQL injection, prompt injection, secret scanning, OWASP compliance — all from Duo Chat. No install, no config, no context switching.
Our March 24 vulnerability audit uncovered 217 threats across 12 sources. Here's what we found, what we shipped to stop it, and how 1-SEC's single-binary architecture keeps you protected without bolting on extra dependencies.
AI agents need third-party API access to be useful, but handing them raw OAuth tokens is a security nightmare. Here's how Auth0 Token Vault and 1-SEC's AI Containment module work together to enable secure, monitored, revocable token delegation for autonomous agents.
AI agents are under siege — 341 malicious skills on ClawHub, CVE-2026-25253, the Moltbook breach, $1.78M lost at Moonwell, and credential leaks across every major framework. Today we ship a SKILL.md that lets any AI agent install full-stack security on its own host in one command.
We audited the entire 2025-2026 prompt injection landscape, found 9 gaps in our detection, added 16 new regex patterns, and built a 750-line multimodal scanner that catches hidden injections in images, PDFs, and HTML — all in pure Go with zero ML dependencies.
The OWASP Top 10 for Agentic Applications 2026 identifies critical vulnerabilities in autonomous AI systems. Here's how each risk maps to real attacks and how to defend against them with open source security tooling.
AI agents are browsing the web, ingesting llms.txt endpoints, and making autonomous payments via x402. This creates an entirely new attack surface. Here's how 1-SEC detects and stops agentic web threats with zero external dependencies.