Detection Engineering · Threat Hunting

Evan
Baltman

Evan Baltman

I'm a generalist passionate about finding patterns in the noise. Currently doing detection engineering at GitLab on the Signal Engineering Team, focused on detecting agentic AI-related threats — CVEs in tools like OpenAI's Codex and Anthropic's Claude Code. Outside security, I love learning foreign languages (я учу русский сейчас) and music.

Detection Engineering Agentic AI Threats Threat Hunting GitLab Russian · Language Learning
Evan Baltman and his dog

Writing

3 articles
In Progress · Est. May 2025

Hunting the Ghost in the Machine: Detecting Malicious Exploitation of AI Coding Agents

Agentic AI tools like Claude Code and GitHub Copilot execute arbitrary code, read files, and make network requests on behalf of developers. When threat actors find CVEs in these agents, the attack surface expands dramatically. This piece explores detection strategies, MITRE ATT&CK mappings, and YARA-based hunting rules for AI agent exploitation in enterprise environments.

Coming Soon

Prompt Injection at Scale: Threat Modeling AI-Augmented CI/CD Pipelines

When your CI pipeline can talk to an LLM, a crafted commit message might be enough to exfiltrate secrets. Threat modeling the new attack surface of AI-augmented build systems.

Coming Soon

Detection as Code: Building a SIEM Rule Review Workflow with GitLab

Treating detections like software: version control, peer review, and automated testing for SIEM rules using GitLab's native CI tooling.

Coming Soon

Signal vs. Noise: Tuning Detections in High-Velocity Developer Environments

At GitLab, developers generate enormous amounts of log data. How do you build detections that catch real threats without burning out your team with false positives?

Coming Soon

Learning Russian as an InfoSec Engineer: Notes on Pattern Recognition in Language and Logs

Finding patterns in security telemetry and finding patterns in a foreign language have more in common than you'd think. Reflections on learning Russian while working in detection engineering.