GHSA-c83g-rgw3-j3cx CVE-2026-73089
Browserslist: Unbounded memory growth (no cache eviction) via distinct query results, leading to eventual OOM
- Severity
- 7.5 / 10
- High · CVSS 3.1
- Exploit chance (EPSS)
- 0.66%
- Chance of exploitation in the next 30 days. Higher than 51.39% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-770 Allocation of Resources Without Limits or Throttling
- Fix
4.28.7- Upgrade browserslist to this version or later
Description
Vulnerability Details
File: index.js
Location: cache (browserslist()'s result cache, line ~402) and
parseCache (parseQueries()'s AST cache)
Root Cause
var cache = {}
var parseCache = {}
function browserslist(queries, opts) {
...
var cacheKey = JSON.stringify([queries, context])
if (cache[cacheKey]) return cache[cacheKey]
...
if (!env.env.BROWSERSLIST_DISABLE_CACHE) { cache[cacheKey] = result }
return result
}
function parseQueries(queries) {
var cacheKey = JSON.stringify(queries)
if (cacheKey in parseCache) return parseCache[cacheKey]
var result = parseWithoutCache(QUERIES, queries)
if (!env.env.BROWSERSLIST_DISABLE_CACHE) { parseCache[cacheKey] = result }
...
}
Every distinct (queries, context) pair is cached forever — no size cap,
TTL, or eviction. browserslist.clearCaches() never resets either object
(it only resets node.js's own filesystem caches); the only opt-out is the
BROWSERSLIST_DISABLE_CACHE env var, controlled by the calling
application, not an attacker.
Some short, valid queries amplify this badly. The since <year>-<month>-<day>
query type (/^since (\d+)-(\d+)-(\d+)$/i) accepts any digit
combination — Date.UTC() normalizes rather than rejects out-of-range
values — giving an effectively unbounded space of ~17-byte distinct cache
keys, each of which resolves to (and caches) a result close to the full
~8.5 KB browser list for any sufficiently old year.
Measured Impact
20,000 distinct since <year>-<month>-<day> queries (~330 KB total input,
--expose-gc before/after measurement to rule out uncollected garbage)
retained over 50 MB of heap permanently — roughly 150x
amplification, growing linearly with no cap observed up to 40,000 queries
(52.3 MB).
Attack Scenario
Any long-running process (server, daemon, warm CI worker) that calls
browserslist() with a query value that varies across requests/items and is
influenced, even partially, by external input accumulates one cache entry
per distinct value ever seen. An attacker who can influence that value
across many requests (this is a volumetric attack, unlike the
single-request DoS findings from this same research pass) sends a stream of
cheap, distinct queries (e.g. since 1900-01-01, since 1900-01-02, ...)
until the process runs out of memory and crashes.
Recommended Fix (implemented and verified)
Replace both plain-object caches with Maps bounded to a fixed maximum
entry count, evicting the oldest entry once the cap is reached (Map
preserves insertion order, so .keys().next().value is always oldest):
var CACHE_MAX_ENTRIES = 500
function boundedCacheSet(map, key, value) {
if (map.size >= CACHE_MAX_ENTRIES) {
map.delete(map.keys().next().value)
}
map.set(key, value)
}
var cache = new Map()
var parseCache = new Map()
(read sites changed to .has()/.get(), write sites to boundedCacheSet())
Verification:
NODE_ENV=test npx uvu test .test.js→ 301/301 pass unmodified (test/cache.test.jsexercisesclearCaches()/BROWSERSLIST_DISABLE_CACHEagainstnode.js's separate filesystem caches, unaffected here); confirmed a repeated identical call still returns the cached reference.- Re-ran the memory PoC post-fix: heap stayed flat at ~4.9 MB after 5,000,
10,000, 20,000, and 40,000 distinct
since-date queries (was 10.5 → 16.5 → 28.4 → 52.3 MB pre-fix).
Impact
- Who is affected: Long-running processes calling
browserslist()with query values that vary across requests/items and are influenced by external input. - What an attacker achieves: DoS via eventual out-of-memory crash, given sustained traffic over time (not a single small payload).
- Conditions required: No authentication; requires volume rather than a single request, hence Medium rather than High severity.
Verification Environment
browserslist @ HEAD (== v4.28.6, current latest stable release) under local
Node.js v20.19.5, run with --expose-gc for accurate heap measurement.
Note
Found during a broader review of this codebase in the same research pass that produced GHSA-rrmg-cfrq-23vv (parse.js algorithmic complexity), GHSA-g6p8-hj8g-x889 (baseline regexp ReDoS), GHSA-73wf-gq98-2v4g (normalizeStats crash/prototype write), and GHSA-h633-868p-5rfw (SCOPED_CONFIG__PATTERN ReDoS) — all single-request DoS vectors. This one is different in character (volumetric, not single-request) and is reported separately/scored lower accordingly.
Affected versions
npm
| Package | Vulnerable | Fixed in |
|---|---|---|
| browserslist | <= 4.28.6 |
No fix yet |
| browserslist | < 4.28.7 |
4.28.7 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
browserslist npm → 4.28.7
- npm
npm install browserslist@4.28.7- yarn
yarn add browserslist@4.28.7- pnpm
pnpm add browserslist@4.28.7
Severity breakdown
CVSS 3.1 7.5
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- None
- Availability
- High
Weakness
CWE-770: Allocation of Resources Without Limits or Throttling
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
How to prevent it
- Requirements: Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
- Architecture and Design: Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
- Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
- Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
- Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
- Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
- Architecture and Design, Implementation: If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery. Ensure that all failures in resource allocation place the system into a safe posture.
- Operation, Architecture and Design: Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems. When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users. Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).
References
Advisories
Fixes and patches
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-73wf-gq98-2v4g Browserslist: Uncaught crash / prototype write via untrusted browserslist-stats.json custom stats (normalizeStats) | High | Also affects browserslist |
| GHSA-w8qv-6jwh-64r5 Regular Expression Denial of Service in browserslist | Medium | Also affects browserslist |
| GHSA-62m5-6wh8-28x7 pypdf has possible long runtimes/large memory usage for encrypted PDF files | High | Same weakness, CWE-770 |
| GHSA-9wfm-jcj8-jfv9 russh's SSH agent server is susceptible to unbound allocations via repeated SSH_AGENT_CONSTRAIN_CONFIRM messages | Low | Same weakness, CWE-770 |
| GHSA-4p9f-7p9m-5vfg russh's SSH client is susceptible to unbounded allocations via EXT_INFO packets | Medium | Same weakness, CWE-770 |
| GHSA-x3rh-gjgm-fmqc pypdf has possible large memory usage when parsing cross-reference streams | High | Same weakness, CWE-770 |
| GHSA-8397-8qf6-f2gm vLLM: Phi-4 multimodal audio encoder materializes and retains full attention matrices: a single max-length audio OOM-crashes the vLLM engine | Medium | Same weakness, CWE-770 |
| EEF-CVE-2026-116078 HTTP/2 request bodies made of 1-byte DATA frames amplify memory use in Bandit | Not rated yet | Same weakness, CWE-770 |
Credits: iaohkut-from-NightWolf-Team
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