44%
of AI code generation tasks introduced a security vulnerability in testing.
Source: Veracode, 2026 GenAI Code Security Report ↗Offensive security, processes and governance for the age of AI and open source
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One repository. One team. One review process you trust.
Every dependency brings its own. Most of what runs in production was never read by anyone on your team.
Assistants and agents commit at machine speed: plausible code, unreviewed assumptions, packages that may not even exist.
One stolen maintainer token. One install script. It reaches your build before it reaches your changelog.
The evidence
44%
of AI code generation tasks introduced a security vulnerability in testing.
Source: Veracode, 2026 GenAI Code Security Report ↗205,474
unique hallucinated package names across 576,000 samples from 16 LLMs. Each one is a name an attacker can register.
Source: Spracklen et al., USENIX Security 2025 ↗1.23M+
malicious open source packages on record, with open source malware growing 75% in a year.
Source: Sonatype, 2026 State of the Software Supply Chain ↗87%
of audited codebases carried at least one open source vulnerability, 581 on average.
Source: Black Duck, OSSRA 2026 ↗ANTEMUR is a security firm with one obsession: the code inside your product that no one on your team wrote. We attack it the way an adversary would, before an adversary does.
ante murum/ˈan.te ˈmuː.rum/Latin, “before the wall”
The ground in front of the wall, held by the redan: a V-shaped outwork with its point facing the enemy. It takes the assault first. That V is our logo.
Traditional application security guards the wall: your code, your perimeter. The attacks of this decade arrive through what you import and what you generate. That is where we stand. Technology alone does not hold. We also secure the processes and governance around it, from policy to incident response.
Our focus / Front 01
Speed changed. Review did not. We audit what assistants and agents put into your repository, and the tools that put it there.
01Hallucinated and slopsquatted packages
02Insecure defaults in generated code
03Secrets exposed in prompts and output
04Prompt injection against coding agents
05Poisoned rules files and MCP servers
06Excessive agent permissions in CI
Our focus / Front 02
Every package, action and SDK is a trust decision. We map who you really trust, and what happens when that trust breaks.
01Maintainer takeover and token theft
02Typosquatting and dependency confusion
03Malicious install scripts
04Reachable transitive vulnerabilities
05Compromised CI actions and build pipelines
06Abandoned and unowned components
Our focus / Front 03
Secure software does not survive insecure decisions. We structure how your company approves, controls, responds and answers for its risk.
Frameworks we work with
01Security governance, policies and ownership
02Risk management and executive reporting
03Third-party and vendor risk
04AI usage policy and controls
05Access, change and secure development processes
06Incident response plans and tabletop exercises
Core techniques
An SBOM and AI-BOM of what really ships: every component, every origin, every line an agent authored.
$ sbom.cdx.json / ai-bom.json
We trace call paths from your entry points to each vulnerable function, so severity reflects what an attacker can actually reach.
$ entrypoint → sink: reachable
Untrusted input followed from source to sink, through generated and imported code alike.
$ source → sanitizer? → sink
Suspicious packages run in an instrumented sandbox. Network, filesystem and process behavior are recorded, not assumed.
$ postinstall → outbound call → flagged
Prompt injection, tool abuse and context poisoning, aimed at your coding agents and MCP integrations.
$ injection → tool call → impact
Build integrity checked against SLSA: pinned actions, signed artifacts, scoped tokens, verifiable provenance.
$ slsa: build track review
Automation finds candidates. Engineers prove them. No working proof of concept, no place in the report.
$ poc: reproducible
Policies, roles, controls and evidence reviewed against how your company really operates and the frameworks it answers to.
$ control → owner → evidence
Method
We inventory your code, dependencies, agents, pipelines and internal processes.
You receiveExposure map
We run adversary techniques against the real paths into your product.
You receiveAttack log
Every finding comes with reproduction steps and measured impact.
You receiveEvidence report
Fixes, policies and guardrails go into your pipeline. Then we test again.
You receiveHardening plan and retest
Public record
2018
A new maintainer gained publish rights and added a dependency built to steal cryptocurrency wallets.
2020
Attackers compromised the build system. A signed update carried the backdoor to thousands of customers.
2021
One string in a log line meant remote code execution in a library present almost everywhere.
CVE-2021-44228 ↗2024
After years of earning trust as a maintainer, an attacker planted a backdoor in a core compression library.
CVE-2024-3094 ↗2025
A widely used GitHub Action was compromised and exposed CI secrets in workflow logs.
CVE-2025-30066 ↗2025
A self-replicating worm spread across npm using stolen maintainer credentials.
2026
New waves of the worm hit npm again, and copycats followed once its source code leaked.
References
Published only with each client's written authorization.
Start here
Tell us what you ship. We answer with a scope, not a sales deck.