How We Audited and Hardened an Open‑Source Anti‑Bot Engine for Production (Synapse Shield v0.9.3)

Description and use

Synapse Shield v0.9.3 removes factorial‑based DoS, O(N²) keystroke handling, and IP spoofing vulnerabilities, achieving sub‑millisecond performance and resilience to high‑volume attacks.

Problem

Synapse Shield, a self‑hosted bot mitigation engine, had algorithmic and architectural vulnerabilities that could be exploited for denial‑of‑service, performance degradation, and IP spoofing.

Outcome

Execution time for Poisson calculation dropped to <0.1 ms, eliminating CPU starvation even with 100,000 burst counts; keystroke processing became O(1), preventing event‑loop stalls; IP spoofing mitigated via trusted proxy list and IPv6 unwrapping.

Workflow

• Audit code for algorithmic DoS and concurrency bottlenecks
• Identify factorial‑based Poisson calculation and list.pop(0) usage
• Implement O(1) factorial recurrence and short‑circuit cutoff
• Replace list with collections.deque for keystroke handling
• Add SYNAPSE_TRUSTED_PROXIES env var and IPv6 normalisation function
• Test under high request bursts and large typing payloads
• Deploy v0.9.3 and monitor CPU and event‑loop metrics

Evidence

In earlier iterations, the cumulative probability was calculated using: ... math.factorial(i) ...

Source

We switched the queue data structure to collections.deque: ... down_t = pending_downs[k_code].popleft()

Source

Execution time dropped to < 0.1 ms, completely eliminating CPU starvation even under 100,000 incoming burst counts.

Source