Summary
Soup Sieve has Memory Exhaustion via Large Comma-Separated Selector Lists
Full technical description
The CSS selector parser in soupsieve (the CSS selector engine for Beautiful Soup 4) allocates unbounded memory when compiling large comma-separated selector lists. An attacker who can supply a crafted CSS selector string to soupsieve.compile() or Beautiful Soup's .select() / .select_one() can cause the application to allocate hundreds of megabytes of heap memory from a relatively small input, leading to memory exhaustion and denial of service.
To be completely transparent, AI tools helped surface this issue. However, it was independently reproduced and carefully validated. Researchers follow responsible disclosure practices and originally shared this report privately.
A 500 KB selector string triggers allocation of approximately 244 MB of heap memory - a 488x, amplification ratio**.
Details
Affected code: soupsieve/css_parser.py, lines ~204, 925, 1106
The soupsieve CSS parser splits comma-separated selector lists and creates one CSSSelector object per list item. Each CSSSelector object contains parsed selector data structures including SelectorList, Selector, and associated tag/attribute/pseudo-class metadata.
When a selector string such as a,a,a,... (with 250,000 comma-separated items) is passed to sv.compile(), the parser:
- Tokenises the entire string and identifies each comma-delimited segment (line ~1106)
- Parses each segment into a full
Selectorobject with all associated metadata (line ~925) - Stores all parsed selectors in a
SelectorList(line ~204)
Root cause: No limit is enforced on the number of selectors in a comma-separated list. The parser will attempt to parse and store an arbitrary number of selectors, with each selector object consuming approximately 976 bytes of heap memory. The total allocation scales linearly with the number of list items, but the amplification ratio (output memory / input bytes) is extremely high because each single-character selector like a expands into a complex object graph.
Attack surface: Any application that passes user-supplied CSS selectors to soupsieve.compile() or Beautiful Soup's .select() / .select_one().
Proof of Concept
import tracemalloc
import soupsieve as sv
tracemalloc.start()
# Build a 500 KB selector string: "a,a,a,...,a" (250,000 items)
count = 250_000
selector = ",".join("a" for _ in range(count))
print(f"Selector string size: {len(selector):,} bytes ({len(selector) / 1024:.0f} KB)")
# Compile the selector — this allocates ~244 MB
compiled = sv.compile(selector)
current, peak = tracemalloc.get_traced_memory()
tracemalloc.stop()
print(f"Compiled selector count: {len(compiled.selectors):,}")
print(f"Current memory: {current / 1024 / 1024:.1f} MB")
print(f"Peak memory: {peak / 1024 / 1024:.1f} MB")
print(f"Amplification ratio: {peak / len(selector):.0f}x")
# Expected output:
# Selector string size: 499,999 bytes (488 KB)
# Compiled selector count: 250,000
# Current memory: ~244 MB
# Peak memory: ~244 MB
# Amplification ratio: ~488x
Credit
Discovered by a security research team from the University of Sydney, focused on detecting open source software vulnerabilities.
Liyi Zhou: https://lzhou1110.github.io/
Ziyue Wang: https://zyy0530.github.io/
Strick: https://str1ckl4nd.github.io/
Maurice: https://maurice.busystar.org/
Chenchen Yu: https://7thparkk.github.io/
Impact
Severity: High
An attacker can exhaust available memory on any server-side Python application that compiles user-supplied CSS selectors via soupsieve. This can cause:
- OOM kills in containerised deployments (Kubernetes pods, Docker containers) with memory limits
- Swap thrashing on bare-metal servers, degrading performance for all co-located processes
- Process termination via Python's
MemoryErrorexception if the system runs out of addressable memory
| Parameter | Value |
|---|---|
| Input size | ~500 KB selector string |
| Memory allocated | ~244 MB |
| Amplification ratio | ~488Ã, |
| Per-object overhead | ~976 bytes per selector |
| Authentication required | None |
| User interaction required | None |
Scalability of attack: The memory allocation scales linearly - doubling the selector count doubles memory usage. An attacker can tune the payload to exactly exhaust a target's memory limits. Multiple concurrent requests multiply the effect.
Downstream exposure: soupsieve is an automatic dependency of beautifulsoup4, one of the most widely installed Python packages. Any web application accepting CSS selectors from users (e.g., web scraping APIs, content filtering tools, CMS preview features) is potentially affected.
Crafted input forces the application to consume excessive CPU, memory, or other resources, degrading or denying service. Typical impact: denial of service.
CVE-2026-49476 has a CVSS score of 7.5 (High). The vector is network-reachable, no privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (2.8.4); upgrading removes the vulnerable code path.
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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Frequently Asked Questions
- What is CVE-2026-49476? CVE-2026-49476 is a high-severity uncontrolled resource consumption vulnerability in soupsieve (pip), affecting versions <= 2.8.3. It is fixed in 2.8.4. Crafted input forces the application to consume excessive CPU, memory, or other resources, degrading or denying service.
- How severe is CVE-2026-49476? CVE-2026-49476 has a CVSS score of 7.5 (High). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
- Which versions of soupsieve are affected by CVE-2026-49476? soupsieve (pip) versions <= 2.8.3 is affected.
- Is there a fix for CVE-2026-49476? Yes. CVE-2026-49476 is fixed in 2.8.4. Upgrade to this version or later.
- Is CVE-2026-49476 exploitable, and should I be worried? Whether CVE-2026-49476 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 CVE-2026-49476 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 CVE-2026-49476? Upgrade
soupsieveto 2.8.4 or later.