Skip to main content
Vulnerability Database/CVE-2026-88411

CVE-2026-88411: FalkorDB GRAPH.EFFECT DoS Vulnerability

CVE-2026-88411 is a denial of service flaw in FalkorDB Redis module caused by improper error handling in the GRAPH.EFFECT component. This post explains its technical details, affected versions, and mitigation steps.

Published:

CVE-2026-88411 Overview

CVE-2026-88411 is an improper error handling vulnerability in FalkorDB v4.20.1, a graph database implemented as a Redis module. The flaw resides in the GRAPH.EFFECT component, specifically in /effects/effects_apply.c. Unauthenticated remote attackers can trigger a Denial of Service (DoS) condition against the FalkorDB service by sending crafted input that the effect application logic fails to handle safely. The weakness is classified under [CWE-248] Uncaught Exception.

Critical Impact

Remote, unauthenticated attackers can crash or hang the FalkorDB Redis module over the network, disrupting availability of any application relying on it for graph data queries.

Affected Products

  • FalkorDB v4.20.1 (Redis module)
  • The GRAPH.EFFECT command handler in src/commands/cmd_effect.c
  • The effect application logic in /effects/effects_apply.c

Discovery Timeline

  • 2026-09-21 - CVE-2026-88411 published to the National Vulnerability Database (NVD)
  • 2026-09-22 - Last updated in NVD database

Technical Details for CVE-2026-88411

Vulnerability Analysis

FalkorDB exposes graph operations through Redis module commands, including GRAPH.EFFECT, which applies replicated effects on secondary nodes. The effects_apply.c code path does not correctly propagate or contain error states produced while applying an effect. When a malformed or unexpected effect payload is processed, the uncaught error condition terminates the server process or leaves the module in a state that halts further request processing.

The issue is amplified by FalkorDB's role in Redis replication. A divergence between primary and replica state during effect application is not gracefully detected in the vulnerable release, so a single triggering request can bring down the database service handling both direct clients and replicated traffic.

Root Cause

The root cause is missing error handling around effect application and replica-state validation. The command handler does not distinguish between recoverable data errors and fatal conditions, and it does not invoke a divergence guard before applying effects. As a result, exceptions that should be caught and returned to the client instead propagate into a crash or hang.

Attack Vector

Exploitation requires only network reachability to the Redis port exposing the FalkorDB module. No authentication or user interaction is required when Redis is deployed without an ACL or password, which is common in internal environments. An attacker issues a crafted GRAPH.EFFECT command with input that drives effects_apply.c into the unhandled error path, terminating the service.

c
// Security patch in src/commands/cmd_effect.c
// Adds error propagation and replica divergence detection
#include "RG.h"
#include "../errors/errors.h"
#include "../effects/effects.h"
#include "../graph/graphcontext_retrieve.h"
#include "../replication/divergence_guard.h"

// GRAPH.EFFECT command handler
int Graph_Effect

Source: FalkorDB commit 17cb1f8f0

Detection Methods for CVE-2026-88411

Indicators of Compromise

  • Unexpected termination or restart of the Redis process hosting the FalkorDB module, with no preceding administrative action.
  • Repeated GRAPH.EFFECT commands originating from a single client IP in Redis slowlog or monitor output.
  • Replication link resets or full resyncs triggered immediately after malformed graph commands.

Detection Strategies

  • Enable Redis command logging or MONITOR sampling in a test environment to flag GRAPH.EFFECT payloads that deviate from expected serialization formats.
  • Correlate FalkorDB process crashes with network flow records to identify the source of triggering traffic.
  • Alert on abnormal ratios of GRAPH.EFFECT commands relative to GRAPH.QUERY traffic from external or non-application sources.

Monitoring Recommendations

  • Track Redis uptime and used_memory metrics for sudden drops, then pivot to command telemetry for the surrounding window.
  • Monitor replication lag and forced full resyncs on FalkorDB replicas as an early signal of divergence-triggered failures.
  • Capture stderr and core dumps from the FalkorDB process so post-crash analysis can confirm whether the fault originates in effects_apply.c.

How to Mitigate CVE-2026-88411

Immediate Actions Required

  • Upgrade FalkorDB past v4.20.1 to a release that includes the fix from pull request #2247.
  • Restrict network access to the Redis port so only trusted application hosts can send commands.
  • Require Redis authentication and ACLs that limit which clients may issue GRAPH.EFFECT.

Patch Information

The vendor fix is delivered in commit 17cb1f8f0 and pull request #2247, which adds explicit error inclusion (../errors/errors.h) and a replica divergence_guard.h used by the GRAPH.EFFECT handler. The patch detects replica divergence during effect application and forces a full resync instead of crashing. Review the FalkorDB commit 17cb1f8f0 and the FalkorDB pull request #2247 for the complete change set.

Workarounds

  • Bind the Redis instance to localhost or a private management interface until patching is complete.
  • Use Redis ACLs to deny GRAPH.EFFECT to all clients except the replication user where feasible.
  • Place FalkorDB behind a proxy or firewall rule that filters GRAPH.* traffic to known application source addresses.
bash
# Configuration example: restrict FalkorDB exposure and require auth
# /etc/redis/redis.conf
bind 127.0.0.1 10.0.0.10
protected-mode yes
requirepass <strong-secret>

# Restrict GRAPH.EFFECT to replication user via ACL
user app on >app-secret ~* +@read +graph.query +graph.ro_query -graph.effect
user repl on >repl-secret +psync +replconf +ping +graph.effect

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

Experience the Most Advanced Cybersecurity Platform

See how the world’s most intelligent, autonomous cybersecurity platform can protect your organization today and into the future.