LLMs for Security Teams
Security research needs full model capability. Governance needs control.
OpenAI-compatible API + Policy Gateway lets you run high-signal security workflows while enforcing your own rules: redact, rewrite, escalate, audit.
Why standard LLMs fail red teams
- Refusals derail automated pipelines and produce inconsistent results.
- Provider moderation changes create regressions you can't control.
- Lack of auditability creates client-trust issues.
- Data retention and training concerns block procurement.
- Multi-tenant controls are hard to implement yourself.
Abliteration gives you full capability and an enforcement layer you control.
How Abliteration helps
Outcome-driven capabilities mapped to your security workflow needs.
Fewer refusals, more reliable automation
Abliteration is a model-editing approach designed to reduce refusal behavior — more stable than prompt jailbreaking across variations. 3/100 refusal rate on harmful-behaviors eval.
Policy Gateway = your rules, enforced in real time
Policy-as-code with millisecond enforcement. Predictable outcomes: rewrite, redact, escalate, or refuse. Shadow mode, canary rollouts, and auto-rollback.
Audit trails your enterprise clients will accept
Structured decision metadata + SIEM exports to Splunk HEC, Datadog Logs, Elastic, S3, and Azure Monitor. Includes policy_id, user/project tags, reason codes, triggered categories.
Client isolation + quotas by default
Create a project per client. Issue scoped keys. Enforce per-user and per-project quotas. Revoke independently. Every engagement gets its own risk profile.
Privacy-first handling for sensitive engagements
No prompt/output retention by default. Never used for training. Internal network details, vulnerability evidence, and client artifacts stay yours.
Drop-in integration
OpenAI-compatible /v1/chat/completions. Change base URL + key, keep your SDK and request schema. Supports streaming, structured JSON output, and function calling.
Where this fits in your security product
Finding triage at scale
Turn large volumes of scanner outputs into structured summaries, deduped findings, and prioritized remediation narratives.
Report automation
Generate consistent executive summaries, risk narratives, and remediation guidance with a standard format across analysts.
Playbook generation
Create reusable test checklists and verification guidance for security controls — defensive and validation — without leaking sensitive client specifics.
Agentic workflows with governance
Build agents that call internal tools with allowlists and audits for tool calls. Policy Gateway enforces rules on every tool invocation through the MCP guard.
Security research policy example
See the governance knobs. This example demonstrates project isolation, quotas, audit logging, redaction, and escalation — not blunt refusal.
{
"policy_id": "secops-redteam-v2",
"project_id": "client-acme-2026",
"rules": {
"categories": {
"pii_leak": "redact",
"credential_exposure": "redact",
"scope_violation": "escalate",
"exploit_generation": "allow",
"vulnerability_analysis": "allow",
"social_engineering_templates": "escalate"
},
"allowlist": [
"penetration testing",
"vulnerability assessment",
"security audit",
"red team exercise"
],
"denylist": [
"real target names outside scope"
]
},
"quotas": {
"per_user_daily_tokens": 2000000,
"per_project_monthly_tokens": 50000000
},
"audit": {
"enabled": true,
"export": "splunk_hec",
"include_decision_metadata": true
},
"rollout": {
"mode": "enforce",
"shadow_percent": 0,
"canary_percent": 100
}
}30 seconds to value
Works with your current SDK. Change the base URL and API key — everything else stays the same.
import openai, os
client = openai.OpenAI(
base_url="https://api.abliteration.ai/v1",
api_key=os.environ["ABLIT_KEY"],
)
response = client.chat.completions.create(
model="abliterated-model",
messages=[{"role": "user", "content": "Analyze these scan results..."}],
stream=True,
)
for chunk in response:
print(chunk.choices[0].delta.content or "", end="")Trust, boundaries, and acceptable use
Abliteration provides capability + governance. Policy-as-code controls, scoped keys, quotas, audit logs, and SIEM exports give you and your clients the confidence to deploy responsibly.
Pricing built for high-volume security workflows
Replace flaky jailbreak maintenance
Stable model behavior + policy controls mean fewer pipeline failures and less analyst time debugging prompt hacks.
Reduce analyst time on triage and reporting
Automate finding summaries, deduplication, and report generation. Your analysts focus on what matters.
Make governance a product feature
Audit logs and SIEM export aren't overhead — they're a selling point for enterprise clients.
Team plan includes priority throughput for automated pipelines.
Policy Gateway is billed separately and includes audit log retention, unlimited policies/projects, and rollout controls.
Ready to build reliable security automation?
Swap your base URL and start testing. Policy Gateway adds governance when you need it.