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Research

Investigating how systems fail.

I study the trust we place in software: the dependencies we install, the code we review, and the tools we give to AI agents. Here are the findings, disclosures, and defenses that came out of that work.

Co-authored preprints
4

Published on arXiv

Active credited advisories
41

GitHub Advisory Database

Critical-severity advisories
7

Among the active records

Original lockfile research
2019

Extended at Black Hat EU

Citations & h-index on Google Scholar

Research snapshot: Oct 19, 2026. Counts cover the work listed here. Citation totals are available on my Google Scholar profile.

01 / Explore the research

From a finding to a fix, a paper, or a shared practice.

Co-authored preprints

Papers

Research on agent skills, the repeatability of AI security review, and vulnerability remediation.

Industry research · 2019 & 2022

Reports & chapters

Contributions to HTTP Archive’s Web Almanac and Snyk’s State of Open Source Security report.

Software engineering · Filed 2013

Patents

A patent application connecting manual testing, screen states, and contextual software localization.

Coordinated vulnerability disclosure

CVEs & advisories

Publicly credited disclosures across developer tooling, web packages, runtimes, and MCP servers.

Software supply chain · 2019 →

Lockfile injection

Original 2019 research, lockfile-lint, and the GitLab work that extended it at Black Hat Europe 2021.

Developer security guidance · 2019 →

npm security

The original npm security best practices, their adoption by OWASP, and ongoing package-manager guidance.

AI & agentic security · 2025 →

AI & agents

Agent skill ecosystem threats, MCP vulnerability disclosures, and benchmarks for AI security tools.

Incident analysis & defensive tooling · 2018 →

Supply chain

The event-stream post-mortem, source-code defenses, and tools that turn research into development safeguards.

02 / Recent papers

Co-authored research, with the full methods and evidence.

All papers

October 2026 · arXiv preprint

How Deterministic SAST and AI Security Agents Divide the Work: Coverage, Harness Policy and Cost in Snyk VulnBench 2.0

An evaluation of deterministic SAST and AI security agents on 108 vulnerabilities across 20 open-source applications, examining coverage, harness policy, and cost. Snyk Code and Claude Code’s strongest evaluated configuration together covered 101 of 108 vulnerabilities.

Liran Tal, Chris Liu, Charlotte Fereday, Sebastian Roth, and Brian Clark

Reports & chapters

Explore reports & chapters

HTTP Archive · · Co-author

Web Almanac 2022 — Security

A data-driven chapter examining web security adoption, including transport security, cookies, security headers, browser protections, and correlations with technology stacks and website popularity.

Saptak Sengupta, Liran Tal, and Brian Clark

Snyk · · Research contributor · Analysis author

State of Open Source Security 2019

Research into vulnerabilities in indirect dependencies and the challenges of remediation. The linked analysis is part of Snyk’s annual report and includes a link to the complete report.

Liran Tal — author of the linked indirect-dependency analysis, published as part of the report.

03 / Research in practice

What happens after publication matters, too.

From lockfiles to Black Hat

GitLab’s Dennis Appelt and Greg Johnson extended my 2019 lockfile injection research to more techniques and ecosystems, presenting their work at Black Hat Europe 2021.

Follow the research trail

A foundation for OWASP guidance

The npm security best practices I co-authored with Juan Picado became the original basis of OWASP’s NPM Security Cheat Sheet.

Read about the OWASP connection