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

Описание и применение

Synapse Shield v0.9.3 устраняет уязвимости, связанные с факториальными вычислениями, списковыми операциями и IP‑спуфингом, обеспечивая устойчивость к DoS и высокую производительность.

Задача

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.

Результат

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.

Рабочий процесс

• 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

Доказательства

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

Источник

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

Источник

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

Источник