Summary
GeoLens's authorization and cache-scope flaws disclose private dataset data and metadata to unauthorized users (fixed in 1.2.4)
GeoLens 1.2.4 fixes a set of vulnerabilities, the most serious of which allow authenticated or anonymous users to obtain data and metadata for datasets they are not authorized to access.
Workarounds
None for the authorization/cache disclosure flaws, upgrading is required. The SSRF and STAC-DoS surfaces can be partially mitigated at the network/proxy layer (egress filtering to block link-local metadata addresses; a request-size limit on POST /search), but the code fix is the durable remedy.
References
- Release: https://github.com/geolens-io/geolens/releases/tag/v1.2.4
- Pull request: https://github.com/geolens-io/geolens/pull/243
- Prior related advisory: GHSA-p23g-mvhj-jh3j
Impact
- Private record metadata disclosure. Record contact, keyword, and distribution sub-resource endpoints did not re-authorize the backing dataset, so any authenticated user could read a private record's contact details (PII), keywords, and distributions. (Runtime-proven.)
- Private tile data via shared caches. Private raster and vector tiles were served with shared-cache (
Cache-Control: public) headers, so a shared cache (a CDN or the bundled reverse proxy) could retain private tile bytes and replay them to later unauthenticated requests, including unpublished public-dataset previews. - Private dataset title enumeration. The map visibility-check endpoint did not authorize read access to the map, allowing any editor to enumerate the titles of non-public datasets in any map by ID, including private maps owned by other users.
- SSRF via DNS rebinding. URL validation for user-supplied service URLs (probes, STAC/OGC API sources, manifest downloads) resolved DNS once and then let the HTTP client re-resolve at connect time, allowing a low-TTL domain to pass validation as a public address and connect to an internal/metadata address.
- Token leak + header injection in service preview. The remote-service preview path passed the authorization token to GDAL via the process environment without sanitization, leaking it through
/proc/<pid>/environand allowing CRLF header injection. - Unauthenticated STAC search DoS.
POST /searchdid not cap the size of GeoJSONintersectsgeometries (theGETsibling did). - API key written to access logs. The bundled reverse proxy logged the
api_keyquery-string credential in cleartext. - Security posture coupled to a logging flag. API documentation exposure and the Secure flag on the OAuth session cookie were keyed off the
LOG_JSONlogging flag rather than an explicit environment setting, so a production deployment at the default could expose/docsand emit a non-Secure session cookie. - Missing Content-Security-Policy (defense-in-depth). The web application shipped no
script-src/default-srcCSP, leaving no containment for token exfiltration if an XSS issue were introduced. - Weak default install credentials. The installer kept the published default database password and could silently retain the default admin password on a headless install.
Crafted input forces the application to consume excessive CPU, memory, or other resources, degrading or denying service. Typical impact: denial of service.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
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See it in your environmentNew to Kodem? Get a demo →Remediation advice
Upgrade to GeoLens 1.2.4. No configuration changes are required for the authorization and cache fixes. Operators on a public, TLS-terminated deployment should additionally set ENVIRONMENT=production to make the production security posture explicit; deployments that do not set it retain their prior behavior.
Frequently Asked Questions
- What is GHSA-P77J-G7H5-R2VW? GHSA-P77J-G7H5-R2VW is a high-severity uncontrolled resource consumption vulnerability in geolens (pip), affecting versions < 1.2.4. It is fixed in 1.2.4. Crafted input forces the application to consume excessive CPU, memory, or other resources, degrading or denying service.
- Which versions of geolens are affected by GHSA-P77J-G7H5-R2VW? geolens (pip) versions < 1.2.4 is affected.
- Is there a fix for GHSA-P77J-G7H5-R2VW? Yes. GHSA-P77J-G7H5-R2VW is fixed in 1.2.4. Upgrade to this version or later.
- Is GHSA-P77J-G7H5-R2VW exploitable, and should I be worried? Whether GHSA-P77J-G7H5-R2VW is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether GHSA-P77J-G7H5-R2VW is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix GHSA-P77J-G7H5-R2VW? Upgrade
geolensto 1.2.4 or later.