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Veria AI is an autonomous pentester: it maps your entire attack surface, proves real exploits, and drafts the fix.
It finds what the annual security review misses, in hours instead of weeks.
“We paid roughly 6 figures for an audit from a top security firm. Veria costs us significantly less and found the same bugs and more.”
What Veria finds, how it proves it, and how it helps you fix it.
Every finding across your repos in one live view, ranked by what's actually exploitable.
Findings post to Slack and file to Linear, with status kept in sync.
Every finding comes with a working exploit, run against your staging environment.
Veria writes the patch and opens the PR with checks passing; all that's left is review and merge.
Veria catches the flaws that slip past human review, and leaves the fix inline.
"import sys, runpy; sys.path.insert(0, 'tools/owners'); runpy.run_module('posthog_owners', run_name='__main__')" const result = spawnSync(python, ['-c', launcher], { const result = spawnSync(python, ['-I', '-c', launcher], { input: filenames.join('\n'), The python -c invocation retains the current repository directory on sys.path immediately after tools/owners. An attacker can land an unprotected root-level yaml.py or yaml/__init__.py, then have it imported instead of PyYAML by a future pull_request_target run and read the app token from GITHUB_TOKEN. Run Python in isolated mode so the working directory and environment-provided import paths are excluded.
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