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Drafts a 4-6 page federal agency white paper for pre-solicitation positioning across five variants (DARPA / DoD /…
Drafts a 4-6 page federal agency white paper for pre-solicitation positioning across five variants (DARPA / DoD / IC BAA, DOE FOA / national lab concept paper, FAR 15.6 civilian unsolicited proposal, SBIR / STTR Phase I concept paper, generic agency white paper), producing a full draft with cover, exec summary, agency-perspective problem statement, proposed technical approach with prior-art comparison and TRL framing, capability summary, past performance, differentiators, optional ROM, and conclusion, plus a separate revision-suggestions checklist covering strengthening, gap remediation, variant checks, tone audit, and tool routing. Triggers on phrases like "white paper drafting", "BAA white paper", "DARPA white paper", "DOE FOA white paper", "SBIR Phase I white paper", "unsolicited proposal", "FAR 15.6 white paper", and "draft a white paper for [agency]". Use when a capture lead needs a shaping-grade technical positioning document ahead of a formal solicitation, not a multi-section RFI response.
Ships as one download · white-paper-drafting.zip · 8 files
A redacted example of what this tool produces — so you can judge the quality before you buy.
Redacted, illustrative example. Rates, names, and figures are fictional placeholders — for internal estimate illustration only.
Variant: darpa_baa. Two artifacts follow: Part 1 — White Paper Draft (abbreviated), Part 2 — Revision Suggestions (abbreviated). DISTRIBUTION STATEMENT A appears on the cover and every page footer per the variant rule.
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COVER PAGE
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Northwind Technical Services LLC
WHITE PAPER
Title: Differential-Privacy Attention Masking for Machine-Speed Threat Classification
Submitted to:
DARPA / I2O — Cyber Hunt at Scale (DARPA-BAA-26-04)
Submitted: 2026-05-22
Submitter:
Northwind Technical Services LLC
UEI: NWTS1234ABCD | CAGE: 7K2Q9
Primary NAICS: 541512 | Business Size: Small Business (SDVOSB)
Address: [REDACTED], VA | FCL: Secret
POC: [REDACTED], Chief Scientist | [email REDACTED] | [phone REDACTED]
Classification: UNCLASSIFIED
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.
DARPA's Information Innovation Office (I2O) Cyber Hunt at Scale program targets the gap between human-led hunt teams and the volume of network telemetry generated by DoD tactical and operational networks; current automated detection systems trade recall for precision and miss slow-moving, signature-evading adversaries. Northwind Technical Services LLC proposes differential-privacy attention masking for threat-token classification at machine speed — masking training-set tokens at inference time to defeat signature-leakage evasion while preserving classification accuracy. Northwind has demonstrated the approach at TRL 4 under prior work (PP-1) and authored peer-reviewed publications in adversarial ML hardening. The proposed next step is a technical exchange with the I2O program manager and submission of a full proposal upon encourage feedback.
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2.1 Agency mission context. DARPA's Cyber Hunt at Scale program (DARPA-BAA-26-04) seeks "autonomy-capable detection systems that operate at machine speed without unacceptable false-positive rates," framed against the I2O FY26 priority of closing the adversary-defender asymmetry in tactical cyber operations.
2.2 Specific problem. Hunt teams cannot scale manually to telemetry volumes on a tactical network. Slow-moving, signature-evading actors (living-off-the-land techniques) defeat current automated detection at rates exceeding 60% under emulated-adversary corpus evaluation.
2.3 Why current approaches fall short. Current approaches rely on full-context transformer scoring or signature-based detection; both leak training-data signatures detectable by adaptive adversaries, enabling evasion.
3.2 Key innovations (with prior-art comparison).
INNOVATION 1: Differential-privacy attention masking eliminates signature-leakage at inference. PRIOR ART: Full-context transformer scoring (representative 2021-2022 commercial detectors). DELTA: Those approaches expose token-level attention weights an adaptive adversary can probe; masking removes the exposed surface while holding classification accuracy within [N]% of the unmasked baseline.
3.3 Technical risks and mitigations.
RISK 1: Masking may degrade recall on rare attack classes. MITIGATION: Stratified evaluation against an emulated-adversary corpus with per-class recall floors; mask aggressiveness tuned per class.
3.5 TRL progression. CURRENT TRL: 4 (validated against an emulated-adversary corpus). EVIDENCE: prototype demo + peer-reviewed publication (PP-1). TARGET TRL at end of effort: 6.
PP-1: DoD / DARPA / I2O — Contract # [number withheld] — Period 2023-04 to 2025-03 — Value $[X]M. Scope: adversarial ML hardening for detection pipelines. Outcome: TRL 4 prototype demonstrated. Relevance to this Concept: directly establishes the masking technique and the evaluation corpus reused here.
DISCRIMINATOR 1: Demonstrates signature-leakage resistance under adaptive-adversary evaluation — proof: PP-1 prototype + IEEE publication.
[END OF PART 1 — WHITE PAPER DRAFT] DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.
## Part 2 — Revision Suggestions
REVISION SUGGESTIONS — Differential-Privacy Attention Masking Variant: darpa_baa | Target: DARPA / I2O | Submitter: Northwind Technical Services LLC
### Block 1 — Strengthening
- STRENGTHEN 1: Section 3.2 Innovation 1 prior-art comparison would be stronger with one additional recent evasion study to broaden the prior-art base. WHERE: Section 3.2. EFFORT: Low. WHY: broader prior-art breadth hardens the DARPA innovative-claims evaluation.
- STRENGTHEN 2: Section 5 PP-1 outcome lists TRL 4 but no quantified accuracy delta. Add the per-class recall figure. WHERE: Section 5. EFFORT: Low.
### Block 2 — Gaps to Address
- GAP 1: Section 3.5 TRL 4 claim cites "emulated-adversary corpus" but not the corpus version/benchmark. REMEDIATION: add corpus version + baseline comparison. CRITICALITY: Important.
### Block 3 — Variant-Specific Checks (darpa_baa)
- [ ] "DARPA hard" framing present in Section 2 (large impact, high technical risk, not commercially available).
- [ ] Every innovative claim in Section 3.2 / Section 6 has explicit prior-art comparison.
- [ ] TRL claim backed by demo / publication / prior contract; target TRL realistic (+1/+2 per phase).
- [ ] Single I2O office targeted.
- [ ] Page cap — total including cover ≤ 7 pages.
- [ ] DISTRIBUTION STATEMENT A on cover and every page footer.
### Block 4 — Tone Checks
- [ ] Problem Statement opens in agency voice, not vendor identity.
- [ ] No PROM language ("we will deliver", "the contractor shall", "upon award").
- [ ] Banned marketing words absent (leverage, best-in-class, revolutionary, paradigm-shifting, next-generation without TRL, etc.).
- [ ] Risks stated honestly; no "guaranteed" / "100% success".
- [ ] Call to action phrased as "the proposed next step is..." not "you must...".
### Block 5 — Next Steps
- If DARPA releases an RFI / Sources Sought, route to the RFI flagship skill (Tool #27).
- On an encourage decision, route to the pursuit decision matrix (Tool #28).
- For stronger discriminator language, route to the win-theme workshop (Tool #8).
[END OF PART 2 — REVISION SUGGESTIONS]