debug-buttercup

- Pods in the crs namespace are in CrashLoopBackOff, OOMKilled, or restarting

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Install skill "debug-buttercup" with this command: npx skills add trailofbits/skills/trailofbits-skills-debug-buttercup

Debug Buttercup

When to Use

  • Pods in the crs namespace are in CrashLoopBackOff, OOMKilled, or restarting

  • Multiple services restart simultaneously (cascade failure)

  • Redis is unresponsive or showing AOF warnings

  • Queues are growing but tasks are not progressing

  • Nodes show DiskPressure, MemoryPressure, or PID pressure

  • Build-bot cannot reach the Docker daemon (DinD failures)

  • Scheduler is stuck and not advancing task state

  • Health check probes are failing unexpectedly

  • Deployed Helm values don't match actual pod configuration

When NOT to Use

  • Deploying or upgrading Buttercup (use Helm and deployment guides)

  • Debugging issues outside the crs Kubernetes namespace

  • Performance tuning that doesn't involve a failure symptom

Namespace and Services

All pods run in namespace crs . Key services:

Layer Services

Infra redis, dind, litellm, registry-cache

Orchestration scheduler, task-server, task-downloader, scratch-cleaner

Fuzzing build-bot, fuzzer-bot, coverage-bot, tracer-bot, merger-bot

Analysis patcher, seed-gen, program-model, pov-reproducer

Interface competition-api, ui

Triage Workflow

Always start with triage. Run these three commands first:

1. Pod status - look for restarts, CrashLoopBackOff, OOMKilled

kubectl get pods -n crs -o wide

2. Events - the timeline of what went wrong

kubectl get events -n crs --sort-by='.lastTimestamp'

3. Warnings only - filter the noise

kubectl get events -n crs --field-selector type=Warning --sort-by='.lastTimestamp'

Then narrow down:

Why did a specific pod restart? Check Last State Reason (OOMKilled, Error, Completed)

kubectl describe pod -n crs <pod-name> | grep -A8 'Last State:'

Check actual resource limits vs intended

kubectl get pod -n crs <pod-name> -o jsonpath='{.spec.containers[0].resources}'

Crashed container's logs (--previous = the container that died)

kubectl logs -n crs <pod-name> --previous --tail=200

Current logs

kubectl logs -n crs <pod-name> --tail=200

Historical vs Ongoing Issues

High restart counts don't necessarily mean an issue is ongoing -- restarts accumulate over a pod's lifetime. Always distinguish:

  • --tail shows the end of the log buffer, which may contain old messages. Use --since=300s to confirm issues are actively happening now.

  • --timestamps on log output helps correlate events across services.

  • Check Last State timestamps in describe pod to see when the most recent crash actually occurred.

Cascade Detection

When many pods restart around the same time, check for a shared-dependency failure before investigating individual pods. The most common cascade: Redis goes down -> every service gets ConnectionError /ConnectionRefusedError -> mass restarts. Look for the same error across multiple --previous logs -- if they all say redis.exceptions.ConnectionError , debug Redis, not the individual services.

Log Analysis

All replicas of a service at once

kubectl logs -n crs -l app=fuzzer-bot --tail=100 --prefix

Stream live

kubectl logs -n crs -l app.kubernetes.io/name=redis -f

Collect all logs to disk (existing script)

bash deployment/collect-logs.sh

Resource Pressure

Per-pod CPU/memory

kubectl top pods -n crs

Node-level

kubectl top nodes

Node conditions (disk pressure, memory pressure, PID pressure)

kubectl describe node <node> | grep -A5 Conditions

Disk usage inside a pod

kubectl exec -n crs <pod> -- df -h

What's eating disk

kubectl exec -n crs <pod> -- sh -c 'du -sh /corpus/* 2>/dev/null' kubectl exec -n crs <pod> -- sh -c 'du -sh /scratch/* 2>/dev/null'

Redis Debugging

Redis is the backbone. When it goes down, everything cascades.

Redis pod status

kubectl get pods -n crs -l app.kubernetes.io/name=redis

Redis logs (AOF warnings, OOM, connection issues)

kubectl logs -n crs -l app.kubernetes.io/name=redis --tail=200

Connect to Redis CLI

kubectl exec -n crs <redis-pod> -- redis-cli

Inside redis-cli: key diagnostics

INFO memory # used_memory_human, maxmemory INFO persistence # aof_enabled, aof_last_bgrewrite_status, aof_delayed_fsync INFO clients # connected_clients, blocked_clients INFO stats # total_connections_received, rejected_connections CLIENT LIST # see who's connected DBSIZE # total keys

AOF configuration

CONFIG GET appendonly # is AOF enabled? CONFIG GET appendfsync # fsync policy: everysec, always, or no

What is /data mounted on? (disk vs tmpfs matters for AOF performance)

kubectl exec -n crs <redis-pod> -- mount | grep /data kubectl exec -n crs <redis-pod> -- du -sh /data/

Queue Inspection

Buttercup uses Redis streams with consumer groups. Queue names:

Queue Stream Key

Build fuzzer_build_queue

Build Output fuzzer_build_output_queue

Crash fuzzer_crash_queue

Confirmed Vulns confirmed_vulnerabilities_queue

Download Tasks orchestrator_download_tasks_queue

Ready Tasks tasks_ready_queue

Patches patches_queue

Index index_queue

Index Output index_output_queue

Traced Vulns traced_vulnerabilities_queue

POV Requests pov_reproducer_requests_queue

POV Responses pov_reproducer_responses_queue

Delete Task orchestrator_delete_task_queue

Check stream length (pending messages)

kubectl exec -n crs <redis-pod> -- redis-cli XLEN fuzzer_build_queue

Check consumer group lag

kubectl exec -n crs <redis-pod> -- redis-cli XINFO GROUPS fuzzer_build_queue

Check pending messages per consumer

kubectl exec -n crs <redis-pod> -- redis-cli XPENDING fuzzer_build_queue build_bot_consumers - + 10

Task registry size

kubectl exec -n crs <redis-pod> -- redis-cli HLEN tasks_registry

Task state counts

kubectl exec -n crs <redis-pod> -- redis-cli SCARD cancelled_tasks kubectl exec -n crs <redis-pod> -- redis-cli SCARD succeeded_tasks kubectl exec -n crs <redis-pod> -- redis-cli SCARD errored_tasks

Consumer groups: build_bot_consumers , orchestrator_group , patcher_group , index_group , tracer_bot_group .

Health Checks

Pods write timestamps to /tmp/health_check_alive . The liveness probe checks file freshness.

Check health file freshness

kubectl exec -n crs <pod> -- stat /tmp/health_check_alive kubectl exec -n crs <pod> -- cat /tmp/health_check_alive

If a pod is restart-looping, the health check file is likely going stale because the main process is blocked (e.g. waiting on Redis, stuck on I/O).

Telemetry (OpenTelemetry / Signoz)

All services export traces and metrics via OpenTelemetry. If Signoz is deployed (global.signoz.deployed: true ), use its UI for distributed tracing across services.

Check if OTEL is configured

kubectl exec -n crs <pod> -- env | grep OTEL

Verify Signoz pods are running (if deployed)

kubectl get pods -n platform -l app.kubernetes.io/name=signoz

Traces are especially useful for diagnosing slow task processing, identifying which service in a pipeline is the bottleneck, and correlating events across the scheduler -> build-bot -> fuzzer-bot chain.

Volume and Storage

PVC status

kubectl get pvc -n crs

Check if corpus tmpfs is mounted, its size, and backing type

kubectl exec -n crs <pod> -- mount | grep corpus_tmpfs kubectl exec -n crs <pod> -- df -h /corpus_tmpfs 2>/dev/null

Check if CORPUS_TMPFS_PATH is set

kubectl exec -n crs <pod> -- env | grep CORPUS

Full disk layout - what's on real disk vs tmpfs

kubectl exec -n crs <pod> -- df -h

CORPUS_TMPFS_PATH is set when global.volumes.corpusTmpfs.enabled: true . This affects fuzzer-bot, coverage-bot, seed-gen, and merger-bot.

Deployment Config Verification

When behavior doesn't match expectations, verify Helm values actually took effect:

Check a pod's actual resource limits

kubectl get pod -n crs <pod-name> -o jsonpath='{.spec.containers[0].resources}'

Check a pod's actual volume definitions

kubectl get pod -n crs <pod-name> -o jsonpath='{.spec.volumes}'

Helm values template typos (e.g. wrong key names) silently fall back to chart defaults. If deployed resources don't match the values template, check for key name mismatches.

Service-Specific Debugging

For detailed per-service symptoms, root causes, and fixes, see references/failure-patterns.md.

Quick reference:

  • DinD: kubectl logs -n crs -l app=dind --tail=100 -- look for docker daemon crashes, storage driver errors

  • Build-bot: check build queue depth, DinD connectivity, OOM during compilation

  • Fuzzer-bot: corpus disk usage, CPU throttling, crash queue backlog

  • Patcher: LiteLLM connectivity, LLM timeout, patch queue depth

  • Scheduler: the central brain -- kubectl logs -n crs -l app=scheduler --tail=-1 --prefix | grep "WAIT_PATCH_PASS|ERROR|SUBMIT"

Diagnostic Script

Run the automated triage snapshot:

bash {baseDir}/scripts/diagnose.sh

Pass --full to also dump recent logs from all pods:

bash {baseDir}/scripts/diagnose.sh --full

This collects pod status, events, resource usage, Redis health, and queue depths in one pass.

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