docs: fix formatting in grant materials

docs/grants/aisi-challenge-fund.md

@@ -190,13 +190,13 @@ The UK AI Safety Institute's mandate includes developing tools and techniques fo
 
 | Week | Activity | Deliverable |
 |------|----------|-------------|
-| 1--2 | Security audit scoping and vendor selection | Signed statement of work with audit firm |
-| 3--6 | Security audit execution | Draft audit report |
-| 4--7 | Red team engagement (overlaps with audit) | Adversarial payload dataset and evasion report |
-| 7--8 | Audit remediation | Patched codebase; verification by auditor |
-| 8--11 | ML model hardening (adversarial retraining) | Updated ONNX model with evaluation metrics |
-| 9--12 | Documentation and integration guides | Published documentation on GitHub |
-| 12--13 | Integration testing of hardened system | Regression test results; updated CI |
+| 1-2 | Security audit scoping and vendor selection | Signed statement of work with audit firm |
+| 3-6 | Security audit execution | Draft audit report |
+| 4-7 | Red team engagement (overlaps with audit) | Adversarial payload dataset and evasion report |
+| 7-8 | Audit remediation | Patched codebase; verification by auditor |
+| 8-11 | ML model hardening (adversarial retraining) | Updated ONNX model with evaluation metrics |
+| 9-12 | Documentation and integration guides | Published documentation on GitHub |
+| 12-13 | Integration testing of hardened system | Regression test results; updated CI |
 | 14 | Final report and public release | v2.0 release with audit attestation; final grant report |
 
 ---
@@ -205,10 +205,10 @@ The UK AI Safety Institute's mandate includes developing tools and techniques fo
 
 | Risk | Likelihood | Impact | Mitigation |
 |------|-----------|--------|------------|
-| Audit identifies critical vulnerabilities | Medium | High | Budget includes remediation time (Weeks 7--8). Responsible disclosure policy already in place. |
+| Audit identifies critical vulnerabilities | Medium | High | Budget includes remediation time (Weeks 7-8). Responsible disclosure policy already in place. |
 | Red team discovers fundamental bypass class | Low | High | ML hardening phase specifically addresses adversarial evasion. Ensemble architecture provides defence in depth. |
 | ML retraining degrades benign accuracy | Medium | Medium | Evaluation on held-out benign test set before model promotion. A/B comparison with current model. |
-| Timeline slippage due to audit vendor scheduling | Medium | Low | Vendor engagement begins Week 1. Buffer built into Week 12--13 integration phase. |
+| Timeline slippage due to audit vendor scheduling | Medium | Low | Vendor engagement begins Week 1. Buffer built into Week 12-13 integration phase. |
 
 ---
 

docs/grants/huntr-registration.md

@@ -94,7 +94,7 @@ Researchers should focus on the following vulnerability categories, which are mo
 
 Use the following severity classification when submitting reports. Huntr may adjust severity during triage.
 
-### Critical (CVSS 9.0--10.0)
+### Critical (CVSS 9.0-10.0)
 
 A complete detection bypass that allows a prompt injection payload to pass through PIF undetected (no block, no flag, no log) when detection is enabled and correctly configured.
 
@@ -105,7 +105,7 @@ A complete detection bypass that allows a prompt injection payload to pass throu
 
 **Impact:** Any application relying on PIF for prompt injection defence is completely unprotected.
 
-### High (CVSS 7.0--8.9)
+### High (CVSS 7.0-8.9)
 
 A partial detection bypass or a vulnerability that significantly degrades PIF's security posture.
 
@@ -117,7 +117,7 @@ A partial detection bypass or a vulnerability that significantly degrades PIF's
 
 **Impact:** Reduced detection effectiveness or unauthorised access to PIF functionality.
 
-### Medium (CVSS 4.0--6.9)
+### Medium (CVSS 4.0-6.9)
 
 Denial of service or information disclosure that doesn't directly enable prompt injection bypass.
 
@@ -129,7 +129,7 @@ Denial of service or information disclosure that doesn't directly enable prompt
 
 **Impact:** Service disruption or information leakage that aids further attacks.
 
-### Low (CVSS 0.1--3.9)
+### Low (CVSS 0.1-3.9)
 
 Hardening recommendations and minor issues that don't have a direct security impact.
 

docs/grants/nlnet-ngi-zero.md

@@ -63,7 +63,7 @@ PIF is a functioning, released project with the following characteristics:
 
 The grant will fund four work packages that harden PIF for broader adoption and extend its detection capabilities.
 
-**WP1: Adversarial Robustness Testing (Weeks 1--4)**
+**WP1: Adversarial Robustness Testing (Weeks 1-4)**
 
 Systematic evaluation of the detection engines against adversarial evasion techniques:
 
@@ -72,7 +72,7 @@ Systematic evaluation of the detection engines against adversarial evasion techn
 - Identify and document bypass vectors.
 - Deliverable: Adversarial test suite (open-source), evasion report, baseline metrics.
 
-**WP2: Detection Engine Expansion (Weeks 3--8)**
+**WP2: Detection Engine Expansion (Weeks 3-8)**
 
 Extend detection capabilities to cover emerging attack vectors:
 
@@ -81,15 +81,15 @@ Extend detection capabilities to cover emerging attack vectors:
 - **ML model retraining:** Adversarial training using payloads from WP1. Evaluation on held-out test sets to ensure benign accuracy is maintained.
 - Deliverable: Updated regex pattern set, retrained ONNX model, evaluation report.
 
-**WP3: Security Audit (Weeks 6--10)**
+**WP3: Security Audit (Weeks 6-10)**
 
 Independent security review of the codebase:
 
 - Audit scope: proxy request handling, regex engine, ML inference pipeline, configuration parsing, input validation, error handling.
 - Focus on vulnerabilities that could allow detection bypass, denial of service, or information leakage.
 - Deliverable: Audit report, remediated codebase, verification by auditor.
 
-**WP4: Documentation and Integration (Weeks 8--12)**
+**WP4: Documentation and Integration (Weeks 8-12)**
 
 Full documentation to lower the barrier to adoption:
 
@@ -226,7 +226,7 @@ Relevant experience:
 
 ## 11. Notes on NLnet Process
 
-- NLnet proposals are reviewed by an independent committee. Decisions typically take 2--3 months.
+- NLnet proposals are reviewed by an independent committee. Decisions typically take 2-3 months.
 - Funding is disbursed in milestones. Each milestone must be completed and verified before the next payment.
 - NLnet provides mentoring, audit support, and connections to the NGI ecosystem as part of the grant.
 - All funded work must be released under an OSI-approved open-source license (Apache 2.0 qualifies).