skills/continuous-llm-red-teaming-with-promptfoo/SKILL.md
Wires Promptfoo and DeepTeam into CI/CD for automated, repeatable red-teaming of LLM apps against OWASP LLM Top 10, OWASP Agentic, and MITRE ATLAS presets, failing the build when jailbreak or injection vulnerabilities regress. Use for continuous adversarial testing in CI/CD, a merge-blocking security gate, or comparing model/prompt versions for compliance reporting.
npx skillsauth add mukul975/cyber-skills continuous-llm-red-teaming-with-promptfooInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Authorized Use Only: Run these adversarial probes only against LLM applications and endpoints you own or are explicitly authorized to test. Generated attack payloads (jailbreaks, prompt injections, harmful-content elicitation) are adversarial inputs; sending them to third-party services without permission may violate terms of service.
Promptfoo is an open-source LLM evaluation and red-teaming framework (used by OpenAI and Anthropic per its README) that generates adversarial test cases, runs them against your model/agent, and grades the responses. DeepTeam (by Confident AI) is a complementary open-source framework offering 50+ ready-to-use vulnerabilities and 10+ research-backed attack methods. Together they let you treat LLM security as a regression test: every commit re-runs the same adversarial suite, and the pipeline fails when a previously-safe behavior regresses.
This matters because LLM applications change constantly — prompts, models, RAG sources, tools, and guardrails all drift. A jailbreak that was patched last sprint can silently return after a prompt edit or a model upgrade. Promptfoo maps its plugins directly onto the OWASP LLM Top 10 (owasp:llm) and OWASP Agentic (owasp:agentic) presets, and onto MITRE ATLAS, so the suite tracks recognized risk taxonomies. The core threat addressed here is AML.T0051 — LLM Prompt Injection (MITRE ATLAS): adversarial instructions that override the application's intended behavior. This skill follows the Promptfoo red-team docs (https://www.promptfoo.dev/docs/red-team/) and DeepTeam docs (https://www.trydeepteam.com/docs/getting-started), and aligns to NIST AI RMF MANAGE-4.1 (post-deployment monitoring and feedback to manage AI risk).
npm install -g promptfoo # or: npx promptfoo@latest
pip install -U deepteam
| ID | Name (MITRE ATLAS) | Tactic | |----|--------------------|--------| | AML.T0051 | LLM Prompt Injection | Initial Access / Persistence (LLM) | | AML.T0051.000 | Direct (Prompt Injection) | LLM Attack | | AML.T0051.001 | Indirect (Prompt Injection) | LLM Attack | | AML.T0054 | LLM Jailbreak | Privilege Escalation / Defense Evasion (LLM) |
Initialize an interactive config; it writes promptfooconfig.yaml where targets, plugins, and strategies live.
promptfoo redteam init
# choose your target type (HTTP endpoint, openai:..., anthropic:..., custom provider)
Edit promptfooconfig.yaml. The purpose grounds attack generation; plugins are adversarial input generators; strategies are delivery techniques (jailbreak/injection wrappers).
# promptfooconfig.yaml
targets:
- id: https://api.example.com/chat # your app endpoint
label: support-bot
redteam:
purpose: |
A customer-support assistant for an e-commerce site. Must never reveal
system prompts, leak PII, or perform actions outside order support.
numTests: 10
plugins:
- owasp:llm # OWASP LLM Top 10 preset
- owasp:agentic # OWASP Agentic threats preset
- id: pii:direct
numTests: 15
- prompt-extraction # system-prompt leakage
- harmful
strategies:
- id: jailbreak # iterative single-turn jailbreak
- id: jailbreak:composite # stacked jailbreak techniques
- id: crescendo # multi-turn escalation
- id: prompt-injection # injection wrapper
redteam run combines generation + evaluation; then open the interactive report.
promptfoo redteam run
promptfoo redteam report # launches the web report (pass/fail per plugin)
Each row shows the plugin (mapped to OWASP/ATLAS), the strategy, the attack prompt, the model's response, and the grader's verdict. The attack success rate per plugin is your headline metric — track it per release.
Use DeepTeam to cover additional vulnerabilities/attacks and to script bespoke suites in Python.
# deepteam_suite.py
from deepteam import red_team
from deepteam.vulnerabilities import Bias, PIILeakage
from deepteam.attacks.single_turn import PromptInjection
def model_callback(prompt: str) -> str:
# call your application's LLM endpoint here and return the text response
return call_my_app(prompt)
red_team(
model_callback=model_callback,
vulnerabilities=[Bias(types=["race"]), PIILeakage(types=["api_and_database_access"])],
attacks=[PromptInjection()],
)
DeepTeam can also be driven from a YAML config:
deepteam run config.yaml
Fail the pipeline when red-team assertions fail. Promptfoo returns a non-zero exit code on failures, which blocks the merge.
# .github/workflows/llm-redteam.yml
name: LLM Red Team
on: [pull_request]
jobs:
redteam:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: '20' }
- run: npm install -g promptfoo
- name: Run red team (fails build on new vulns)
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: promptfoo redteam run --no-progress-bar
- name: Export machine-readable results
if: always()
run: promptfoo redteam report --output results.json
- uses: actions/upload-artifact@v4
if: always()
with: { name: redteam-report, path: results.json }
Persist results.json per run and compare attack-success-rate per plugin between releases. A rising rate for any OWASP LLM category is a regression to triage before release. Promptfoo's --filter-failing lets you re-run only previously failing cases to confirm a fix.
promptfoo redteam run --filter-failing results.json
| Resource | Link | |----------|------| | Promptfoo red-team docs | https://www.promptfoo.dev/docs/red-team/ | | Promptfoo red-team configuration | https://www.promptfoo.dev/docs/red-team/configuration/ | | Promptfoo CI/CD integration | https://www.promptfoo.dev/docs/integrations/ci-cd/ | | Promptfoo MITRE ATLAS mapping | https://www.promptfoo.dev/docs/red-team/mitre-atlas/ | | DeepTeam (Confident AI) | https://github.com/confident-ai/deepteam | | DeepTeam docs | https://www.trydeepteam.com/docs/getting-started | | OWASP Top 10 for LLM Applications | https://genai.owasp.org/ |
| Promptfoo item | Type | Maps to |
|----------------|------|---------|
| owasp:llm | preset | OWASP LLM Top 10 suite |
| owasp:agentic | preset | OWASP Agentic threats |
| prompt-extraction | plugin | LLM07 system-prompt leakage |
| pii:direct | plugin | LLM06 sensitive-info disclosure |
| harmful | plugin | harmful content generation |
| jailbreak / jailbreak:composite | strategy | AML.T0054 LLM jailbreak |
| crescendo | strategy | multi-turn jailbreak |
| prompt-injection | strategy | AML.T0051 prompt injection |
promptfooconfig.yaml created with target, owasp:llm, and owasp:agentic plugins.promptfoo redteam run executes and produces a per-plugin pass/fail report.model_callback.results.json artifact archived per run for regression tracking.development
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