Status: Stable
Version: 1.0.0
Author: Rifteo
Tags: red-team, pentest, offensive-security, opsec, low-noise, stealth, passive-recon, detection-avoidance
Summary
Run offensive engagements that stay below SOC detection thresholds — passive recon first, active interaction only when necessary, and every active step justified before it is taken.- Activates only when the user explicitly signals stealth as the priority (“stay under the radar”, “avoid the SOC”, “be stealthy”, “ghost mode”, “don’t trigger alerts”)
- Defines a Noise Budget: action categories from “zero cost” to “critical — triggers simultaneous detections”
- Enforces a gated escalation flow: passive → passive exhausted? → minimal targeted active only
- Applies SOC perspective to every proposed action: would a legitimate actor in this environment do this? Would this stand out in a normal day’s logs?
SKILL.md file
Discover skill details
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Less Noise Attack — Low-Noise Offensive Operations
The Core Discipline
- Noise is evidence of presence. Presence without results is pure loss
- Every action you take is a signal. Signals accumulate. Accumulated signals become detections
- The goal is not to be fast — it is to reach the objective without being noticed doing it
- Passive first. Active only when passive is exhausted or insufficient. Targeted active only
- Do exactly what is needed. Never touch what does not need touching. Never scan what can be inferred
Phase 1 — Passive Only
Exhaust passive sources before generating any active signal against the target.What passive recon covers across all engagement types:- Public records: DNS, WHOIS, certificate transparency, ASN/BGP/IP range data
- Infrastructure visibility: passive fingerprinting services that aggregate data without touching the target
- Organizational intelligence: employee enumeration, org structure, technology signals from public job postings, conference talks, public repositories
- Leaked material: public repositories, paste sites, breach data, exposed config files, archived documentation
- Cached intelligence: search engine caches, historical snapshots — endpoints, credentials, internal references, and technology versions that were once publicly accessible
- Relationship mapping: third-party integrations, vendor relationships, supply chain exposure, trust boundaries inferable without active probing
Phase 2 — Gate to Active
Only escalate to active interaction when:- Passive sources do not resolve a specific question the attack plan depends on
- A target has been confirmed and needs validation that passive data cannot provide
- A specific vulnerability hypothesis requires direct interaction to test
- The passive phase has surfaced a high-value target that justifies the exposure cost of touching it
- One target, not a sweep
- One question, not a coverage pass
- One confirmation, not a carpet-bomb of the surface
Noise Budget
Principle: never upgrade the noise level when the current level can produce the answer.
Action Minimalism
Do only what is needed to reach the next decision point.- If one action answers the question, take one action. Not five
- If passive data already resolves something, do not re-confirm it with an active probe
- If a target has been confirmed, interact with what is relevant to the objective — not everything that is exposed
- If a finding is confirmed, document it and move — do not repeat the technique across every adjacent surface looking for more instances
- If a surface yields nothing after a targeted approach, log it and redirect — do not broaden the probe to compensate
Operational Behavior Discipline
When active interaction is unavoidable, control how it looks.Timing:- Introduce natural, variable delays between actions — uniform timing is a machine signature
- Avoid burst patterns — concentrated activity in a short window is statistically anomalous
- Spread enumeration across time when the engagement timeline allows
- Match activity cadence to the target environment’s expected operational rhythm
- Behave the way a legitimate entity in that environment would behave
- Use tooling configured to match normal operational patterns, not default scanner behavior
- Follow the expected interaction flow — skipping steps a real actor would not skip is anomalous
- Any enumeration is rate-limited against what normal operational load looks like in that environment
- Target sets are focused and derived from gathered intelligence — not generic maximum-coverage lists
SOC Perspective — Know What You Look Like
What gets detected first across all domains:- Sweep and scan signatures — high-volume, sequential, or range-based activity
- Repeated failure patterns — failed authentications, failed connections, failed lookups at volume
- Known offensive tool fingerprints — default configurations, timing patterns, known payload signatures
- Behavioral anomalies — activity that does not match the normal operational profile of the environment
- Temporal and geographic anomalies — timing, origin, or access patterns that deviate from baseline
- Lateral movement signatures — access to resources not historically touched together
- Single, deliberate, targeted actions consistent with what a legitimate actor would do
- Activity that follows the expected timing and flow of the environment
- Volume and frequency consistent with normal operational load
Escalation Logic
Detection Recovery
If detection is suspected — an action was blocked, a session was reset, a response was anomalous:- Stop the current action immediately
- Do not retry the same action — repeating a detected action confirms the signature and escalates the response
- Do not pivot to a louder technique to overcome the block
- Analyze what the response reveals about the defensive posture — it is intelligence
- Reassess the approach from a different angle or access path before continuing
- Log what triggered the response — understanding the detection boundary has operational value
Benchmark Results
Tested on claude-sonnet-4-6 via Claude Code CLI. Same engagement brief, same prompt, same model — the only variable is whether the skill is loaded. The brief: a 5-day authorized pentest on a monitored fintech web app with live payment flows, asking for a day-by-day plan that stays under detection.
Without the skill the plan was organized around coverage — it opened by spidering the live target and planned an unbounded IDOR sweep, either of which can trip a fintech’s monitoring on Day 2 and end the engagement. With the skill it was organized around signal-to-noise: passive intelligence first, every active action individually defensible as something a legitimate user would do, enumeration bounded to what proves the pattern, and the noisiest paths replaced or dropped with reasoning.
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