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GHSA-ffq3-xpv3-j92q
No affected components available
Summary
Type: Algorithmic-complexity DoS in reference-link definition handling. A markdown document with N reference-link definitions of the same key (or many distinct keys) takes O(N²) parser time. 5000 repeated [a]: u\n definitions take ~1.1 second; 10000 → ~4.5 seconds.
File: src/mistune/block_parser.py (reference-link def parsing) and the surrounding ref_links env-dictionary handling.
Root cause: every reference definition is parsed by scanning forward from each candidate position. The unikey normalisation runs per-def, the dictionary insert is per-def, and the lookup-by-label-then-iterate-defs path is linear in the number of stored defs. For input with N defs, the total work is O(N²).
Affected Code
src/mistune/block_parser.py — reference-definition rule fires on every line that matches [label]: url. For each one:
unikey(label)is called (linear scan of the label).- The def is appended to
state.env['ref_links']. - Later inline-link resolution looks up by
unikey(label)in the dict (O(1)) but the surrounding parser revisits the def list for paragraph-vs-def disambiguation.
The cumulative parse time grows as the square of the number of defs.
Why it's wrong: the parser does not amortise the def-list scan. A single forward pass with a hash-keyed dict (already in place) plus a per-line classifier should make this O(N).
Exploit Chain
- Application uses mistune to render attacker-supplied markdown. No plugins required.
- Attacker submits a 35 KB document of
[a]: u\nrepeated 5000 times followed by[click][a]. - CPU pegs for ~1.1 seconds. 10000 defs → ~4.5 s. 20000 → ~18 s. Doubling input quadruples time.
Security Impact
Attacker capability: small input → large CPU. Predictable scaling. Can be repeated.
Preconditions: application uses mistune.create_markdown() (default config) on attacker-supplied markdown. Worth noting: the ref_links dictionary persists for the lifetime of the parse, so a long document with many defs builds up memory; with N defs of attacker-chosen length, the per-def normalisation cost compounds.
Differential: PoC-verified against mistune@3.2.1, default config:
import mistune, time
md = mistune.create_markdown()
for n in [1000, 2000, 5000, 10000]:
s = '[a]: u\n' * n + '[click][a]'
t = time.time()
md(s)
print(f' ref defs * {n} ({len(s)}b): {(time.time() - t) * 1000:.0f}ms')
# Output (Python 3.13, Linux, 2.5GHz CPU):
# ref defs * 1000 ( 7012b): 46ms
# ref defs * 2000 (14012b): 186ms
# ref defs * 5000 (35012b): 1121ms
# ref defs * 10000 (70012b): 4400ms
The patched build (with the surrounding parser amortised to O(N)) keeps the time linear.
Suggested Fix
Replace the per-def re-scan with a single forward pass that classifies each line into ref_def | paragraph | other once and only inserts into ref_links once per def. The dict already exists; the wasted work is in the surrounding scan loop, not in the dict operations.
A regression test asserting that md('[a]: u\n' * 50_000 + '[click][a]') completes in under 1 second would catch any regression.
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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