🤖 AI Summary
This study addresses the vulnerability of distributed malware detection systems to endpoint misclassification caused by server failures. To mitigate this, we construct a Promela model based on Bitdefender’s production architecture and formally verify its graceful degradation fallback chain mechanism using the SPIN model checker combined with Linear Temporal Logic (LTL). This work presents the first formal verification of the fault-handling layer within a production-grade security system, thereby bridging a significant research gap in the field. Experimental results demonstrate that the system is free from deadlocks and false positives while guaranteeing unique verdicts, ensuring that degradation behaviors remain orderly and controllable under failure conditions.
📝 Abstract
Modern endpoint malware detection is distributed: a lightweight agent on each endpoint collects features from a scanned file or process, sends them to a remote server for analysis, and then enforces the returned verdict locally by blocking, quarantining, or disinfecting. Because the endpoint acts on the verdict, the distributed machinery surrounding detection must never turn a transient server failure into a wrong action. We present a formal model, in Promela, of the endpoint decision pipeline of such a system, abstracted from a production architecture at Bitdefender. The model captures the system's graceful-degradation fallback chain: when the primary analysis server times out, the endpoint falls back to an older legacy-protocol server, and failing that to a reduced-signature local scan, before enforcing a verdict. Assuming detection signatures are sound, we specify six safety and liveness properties in linear temporal logic (LTL) and verify them exhaustively with the SPIN model checker. We prove that the fallback machinery never causes a false positive (an enforcement action against a benign file), commits to exactly one verdict per scan even when timed-out responses arrive late, weakens detection strength only in an explicit and ordered way, and always terminates in an enforcement decision, so the pipeline is deadlock-free. Each property is checked to hold non-vacuously, and we report how the state space grows with concurrent scans and endpoints. The work shows how model checking can give strong correctness guarantees for the failure-handling logic of a production security system, a layer that has received little direct formal attention.