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Paper Citation Record · LEDGER

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution

As of 9 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2607.22076.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.22076 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:55:25.661951Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

63 of 63 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved62
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5545d04b-6b99-409e-9122-15a8fc9f751f · outbound

This paper cites What are cves? understanding common vul- nerabilities,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution What are cves? understanding common vul- nerabilities,

Reference 1

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source=pdf_text observed=2026-08-01T05:55:20.242618Z digest=sha256:2f195cb148ba2136fc71fccc8fac370b55700ada098d7f3d2bea1e91f5fa9a9c

Observation 1b329e87-7083-47ff-bb7f-a8b555479372 · outbound

This paper cites A large-scale empirical study of security patches,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution A large-scale empirical study of security patches,

Reference 2

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source=pdf_text observed=2026-08-01T05:55:20.318721Z digest=sha256:4a63e02599b473b42e4b65d6018f403bfbfb4fa82a2c397f27f47112f460f90c

Observation d90f7aa8-e4a6-48da-8059-4a19b121093f · outbound

This paper cites Detecting.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Detecting

Reference 3

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source=pdf_text observed=2026-08-01T05:55:20.404073Z digest=sha256:a8f78c0c3c071d1d920ecc20429e402627a9100c280bfcfc8d71921841afadb4

Observation d92aeed5-ea93-420c-bd17-dffd29899ed3 · outbound

This paper cites Finding a needle in a haystack: Automated mining of silent vulnerability fixes,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Finding a needle in a haystack: Automated mining of silent vulnerability fixes,

Reference 4

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source=pdf_text observed=2026-08-01T05:55:20.525228Z digest=sha256:7dc1def1e8dc7e31f8b56bb314d94fbafa69c622b048efd38492011a01bb59cb

Observation 6c5e3ba5-cb77-4e20-b582-64e13e3e79c2 · outbound

This paper cites What lies beneath: an empirical study of silent vulnerability fixes in open-source software,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution What lies beneath: an empirical study of silent vulnerability fixes in open-source software,

Reference 5

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source=pdf_text observed=2026-08-01T05:55:20.649928Z digest=sha256:b4665a094ce87c9d6c68ef5077f02bfe9021d2769d53065bf662d3663ed1b3e6

Observation 2c4fcb81-2127-44ff-be30-76cdb5c2aa44 · outbound

This paper cites Automatic patch- based exploit generation is possible: Techniques and implications,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Automatic patch- based exploit generation is possible: Techniques and implications,

Reference 6

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source=pdf_text observed=2026-08-01T05:55:20.767571Z digest=sha256:42e6d9713a91becdfc3a571a5433b63592b6fe48fff5400dfa0c6af2c9d7b5b8

Observation c29e7c8b-fa0c-488d-b118-aa01d5f3c427 · outbound

This paper cites Scaling javascript abstract interpretation to detect and exploit node. js taint-style vulnerability,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Scaling javascript abstract interpretation to detect and exploit node. js taint-style vulnerability,

Reference 7

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source=pdf_text observed=2026-08-01T05:55:20.886540Z digest=sha256:b5db9716203473e4702a6b0251f2924d6f91acf24e75e2f14a6b2403472fc3aa

Observation 8c3c1170-ea0c-4e63-ace4-cbe7e59bd07b · outbound

This paper cites Automated exploit generation for node. js packages,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Automated exploit generation for node. js packages,

Reference 8

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source=pdf_text observed=2026-08-01T05:55:21.052251Z digest=sha256:a82603e7cfa2f04867ab464a831cd4f10eba2345564f4f9b287cbc89352cba62

Observation bcb97fa2-df47-48eb-ba37-0e71cdfce107 · outbound

This paper cites Nodemedic- fine: Automatic detection and exploit synthesis for node. js vulnerabili- ties.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Nodemedic- fine: Automatic detection and exploit synthesis for node. js vulnerabili- ties

Reference 9

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source=pdf_text observed=2026-08-01T05:55:21.197979Z digest=sha256:b7161de8c85a17771bbca3dcd612af8745173a9163801ab6d10ada753dbe9f64

Observation 3133b505-ff75-41bd-8b65-d55611a628fa · outbound

This paper cites Pocgen: Generating proof- of-concept exploits for vulnerabilities in npm packages,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Pocgen: Generating proof- of-concept exploits for vulnerabilities in npm packages,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-01T05:55:21.370547Z digest=sha256:1b87ee828a72147778bc0d8b00f3a680f57c0b802d4bb4f8ad0ca17ff38fddd2

Observation e7c23847-5a17-4efc-b80b-c0f6bebb443b · outbound

This paper cites Code change intention, development artifact, and history vulnerability: Putting them together for vulnerability fix detection by llm,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Code change intention, development artifact, and history vulnerability: Putting them together for vulnerability fix detection by llm,

Reference 11

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source=pdf_text observed=2026-08-01T05:55:21.509723Z digest=sha256:1e08c755a8917d406e76ddd12f48df07c6620474c5f284cc612d211c0c2bad0a

Observation bf0ed59c-501e-4f9e-bdfd-c25ccc729eee · outbound

This paper cites Not every patch is an island: Llm-enhanced identification of multiple vulnerability patches,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Not every patch is an island: Llm-enhanced identification of multiple vulnerability patches,

Reference 12

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source=pdf_text observed=2026-08-01T05:55:21.619545Z digest=sha256:9f42d44b35583a25c2b3c36271d178abb02b3b9a8dfae5f16325e3c4054a56b9

Observation 192f7fe1-2be6-4b35-b827-f148f70c9f4f · outbound

This paper cites CVE List V5,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution CVE List V5,

Reference 13

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source=pdf_text observed=2026-08-01T05:55:21.750261Z digest=sha256:b2d246e5bd09ca952d49cb3abbffd8452c004c123cee1603121bbe3471d61f16

Observation 71ed3bc8-5e14-4185-a9ec-3004aa1e1ba3 · outbound

This paper cites Large language models are human-level prompt engineers,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Large language models are human-level prompt engineers,

Reference 14

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source=pdf_text observed=2026-08-01T05:55:21.854356Z digest=sha256:0c48197f8dddb96fea7a92064c1f44183f6a145fbb65a2758fbe5990ad7f9223

Observation 717b93ee-c1df-4bc9-8a9d-bbdebf84b52f · outbound

This paper cites Promptbreeder: Self-referential self-improvement via prompt evolution,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Promptbreeder: Self-referential self-improvement via prompt evolution,

Reference 15

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source=pdf_text observed=2026-08-01T05:55:22.009010Z digest=sha256:81e968bcec18b465b9528a34affa752da13ac35103c6f6a3095fad35c6df729c

Observation b693bbbf-e0c2-4d84-a8d2-3aacd3725838 · outbound

This paper cites Self-refine: Iter- ative refinement with self-feedback,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Self-refine: Iter- ative refinement with self-feedback,

Reference 16

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source=pdf_text observed=2026-08-01T05:55:22.170904Z digest=sha256:d2c9d1af86c60e262dd7421dabb74d6809f3b771cbb1a58cb8443a6521cd1dc9

Observation a637a3be-609f-4d71-90b4-b589687957d3 · outbound

This paper cites Re- flexion: Language agents with verbal reinforcement learning,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Re- flexion: Language agents with verbal reinforcement learning,

Reference 17

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source=pdf_text observed=2026-08-01T05:55:22.293050Z digest=sha256:a046025bbe219273473d3b4cd41306a8aa254f10074818d56c66bf154ec2b7ef

Observation 3667c861-4ad8-4301-a22d-0c732c4a110a · outbound

This paper cites Automatic prompt optimization with “gradient descent.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Automatic prompt optimization with “gradient descent

Reference 18

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source=pdf_text observed=2026-08-01T05:55:22.443804Z digest=sha256:dbe37e01b529443a0c8dfa5bd6f616b72d74692053cd7b9f44469e9548174332

Observation 2cbce5d9-51f8-46b7-80c1-f86f61a4c649 · outbound

This paper cites Critic: Large language models can self-correct with tool-interactive critiquing,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Critic: Large language models can self-correct with tool-interactive critiquing,

Reference 19

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source=pdf_text observed=2026-08-01T05:55:22.599875Z digest=sha256:9878db245c65d582c4106b27bc650fe27c353ed4123e86adec4ec97a707a197a

Observation ac921e53-8c4d-400a-affd-c7e8e8d2f5a4 · outbound

This paper cites Large language models as optimizers,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Large language models as optimizers,

Reference 20

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source=pdf_text observed=2026-08-01T05:55:22.766439Z digest=sha256:e364dcdc672ab22fd01ce2f89f4d7d5ad995c51c15b6dded2d81e599d511217d

Observation 66d66c19-a865-490d-9772-83be0f2ef6a5 · outbound

This paper cites GEPA: Reflective prompt evolution can outperform reinforcement learning,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution GEPA: Reflective prompt evolution can outperform reinforcement learning,

Reference 21

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source=pdf_text observed=2026-08-01T05:55:22.927586Z digest=sha256:fd658132463d45ff1b4d3f025595ca285b41611a8ee91292d72b113edb681882

Observation 7899ad22-9fc5-43f0-bb4d-a71b8ff8d5a5 · outbound

This paper cites dirty-json,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution dirty-json,

Reference 22

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source=pdf_text observed=2026-08-01T05:55:23.011703Z digest=sha256:d0c846b0a1b8d90f90d797700934748117021a82ba62ef9f790b33a7fb2ac81b

Observation ca99861b-55d9-484e-b6f6-730db2246937 · outbound

This paper cites dirty-json Vulnerability: Prototype Pollution,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution dirty-json Vulnerability: Prototype Pollution,

Reference 23

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source=pdf_text observed=2026-08-01T05:55:23.016212Z digest=sha256:b15ff3e38e8e174546ca62fd3eb5cc87ef79bd52380f4efbaed87be0e7d57e4a

Observation 36caa297-e6a0-428a-82e8-cc988e67fafb · outbound

This paper cites SSPCatcher: Learning to catch security patches,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution SSPCatcher: Learning to catch security patches,

Reference 24

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source=pdf_text observed=2026-08-01T05:55:23.021244Z digest=sha256:ba21facfeaf07b6aa0748e4c4443399fa4bbce4ce73ca51824e59a55af6e1d81

Observation 4b277036-8175-476d-ae4e-5136a417ac9f · outbound

This paper cites VulCurator: A vulnerability-fixing commit detector,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution VulCurator: A vulnerability-fixing commit detector,

Reference 25

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source=pdf_text observed=2026-08-01T05:55:23.025556Z digest=sha256:ebedc3b0d6fe065c2a6bc989d474e11b221fc881b1203efa48f34ddae8225371

Observation 38f6196f-4ab7-4a96-aea3-f12fe128e439 · outbound

This paper cites SPI: Automated identification of security patches via commits,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution SPI: Automated identification of security patches via commits,

Reference 26

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source=pdf_text observed=2026-08-01T05:55:23.030368Z digest=sha256:b53fb56de006726dba1f8e08d44b146274d6bfb645807922a15af61bb7f1b3fb

Observation b139bb4f-c16c-40cf-95e5-20bb2fcf734f · outbound

This paper cites Semfuzz: Semantics-based automatic generation of proof-of-concept exploits,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Semfuzz: Semantics-based automatic generation of proof-of-concept exploits,

Reference 27

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source=pdf_text observed=2026-08-01T05:55:23.034613Z digest=sha256:edb3455255632cf775eb7b2cde620c26af9d1984f716f314f31289b721471ea3

Observation 49137a31-7ec6-4d55-8e55-33669351225b · outbound

This paper cites Exploiting library vulnerability via migration based automating test generation,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Exploiting library vulnerability via migration based automating test generation,

Reference 28

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source=pdf_text observed=2026-08-01T05:55:23.039169Z digest=sha256:e739d10ab7ed41f5de598716bb3bf7da0956bb27deb47267ff5c4bc9ccf6c320

Observation 7885e386-a05b-4e6e-aa30-369edc0b0544 · outbound

This paper cites Test mimicry to assess the exploitability of library vulnerabilities,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Test mimicry to assess the exploitability of library vulnerabilities,

Reference 29

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source=pdf_text observed=2026-08-01T05:55:23.100397Z digest=sha256:a1651f868317eea07dcab174da5d108c8c26741e5b2b1d10f8ffbb71ada7a2e3

Observation 2f11adeb-b05c-440d-beaa-1e73ae18d1c8 · outbound

This paper cites {APPATCH}: Automated adaptive prompting large language models for{Real-World} software vulnerability patching,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution {APPATCH}: Automated adaptive prompting large language models for{Real-World} software vulnerability patching,

Reference 30

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source=pdf_text observed=2026-08-01T05:55:23.219244Z digest=sha256:2fac6e42714fc5d07b23bd4861464a16706036fe35f4bce59c9fd9f39bd2a6ae

Observation bb2ee55f-d0eb-43d0-9dca-ddbe13e1f382 · outbound

This paper cites Docter: Documentation-guided fuzzing for testing deep learning api functions,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Docter: Documentation-guided fuzzing for testing deep learning api functions,

Reference 31

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source=pdf_text observed=2026-08-01T05:55:23.352716Z digest=sha256:4c1ed77a1c1e4a3461e6c3e33701d7fac590e911fbdadea14e4d999d60c2cb5e

Observation c9068e9f-fc5e-4b5b-9aea-7a03c0a7c2b5 · outbound

This paper cites {CarpetFuzz}: Automatic program option constraint extraction from documentation for fuzzing,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution {CarpetFuzz}: Automatic program option constraint extraction from documentation for fuzzing,

Reference 32

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source=pdf_text observed=2026-08-01T05:55:23.478859Z digest=sha256:d3abd7f593468b45acc87570154134978c805e2efce8ba6aaf02aa014a671fab

Observation ef61abc9-a0b2-4e52-a6e5-95cffc2e9c78 · outbound

This paper cites Learning from the past: Real-world exploit migration for smart contract poc generation,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Learning from the past: Real-world exploit migration for smart contract poc generation,

Reference 33

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source=pdf_text observed=2026-08-01T05:55:23.578193Z digest=sha256:010739562b02e43f139cca9f112e401ca0043da3ebb2bdebd121fbf40fb66b97

Observation b8e90817-bee4-4941-b914-aa2d3efa81f0 · outbound

This paper cites Language models are few-shot learners,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Language models are few-shot learners,

Reference 34

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source=pdf_text observed=2026-08-01T05:55:23.676744Z digest=sha256:00f16f24463429b59140fe93edf9f4f169ce4352665a8ed8575acf03ce5a4e59

Observation fe7ba958-eb62-4fc6-a8f7-77af26c43028 · outbound

This paper cites {ChainFuzz}: Exploiting upstream vulnerabilities in{Open-Source}supply chains,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution {ChainFuzz}: Exploiting upstream vulnerabilities in{Open-Source}supply chains,

Reference 35

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source=pdf_text observed=2026-08-01T05:55:23.844702Z digest=sha256:36fc9a7ffba9ce32fbccdda49c4b59e68a83c1d12d27dcdde7a0c5de972b5082

Observation 7877b147-52c7-4a4c-b192-f4ec33aace32 · outbound

This paper cites {NA VEX}: Precise and scalable exploit generation for dynamic web applications,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution {NA VEX}: Precise and scalable exploit generation for dynamic web applications,

Reference 36

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source=pdf_text observed=2026-08-01T05:55:23.972782Z digest=sha256:545d80b4fcca697e9952df8da6bd2bc72ddd4fada84afa871af3b389c3b79acd

Observation 4c76db4e-24ca-4837-bd06-9e2aa69cd86d · outbound

This paper cites Revery: From proof-of-concept to exploitable,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Revery: From proof-of-concept to exploitable,

Reference 37

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source=pdf_text observed=2026-08-01T05:55:24.058916Z digest=sha256:34e45114f29ee0d0bab6bd5d5aecaeffe3b2f9066ffa4cc47f222131edf0991b

Observation 270df044-54e4-49e5-8272-15d4ae29fba9 · outbound

This paper cites 1dfuzz: Reproduce 1-day vulnerabilities with directed differ- ential fuzzing,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution 1dfuzz: Reproduce 1-day vulnerabilities with directed differ- ential fuzzing,

Reference 38

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source=pdf_text observed=2026-08-01T05:55:24.115107Z digest=sha256:bbe4a9080092df0a0679b88edecaa9a20a5a289d89dbcd0652335aac822e8e2a

Observation 51671f6b-a192-47b3-8106-e2fcdee86469 · outbound

This paper cites Bullseye: Detecting prototype pollution in npm packages with proof of concept exploits,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Bullseye: Detecting prototype pollution in npm packages with proof of concept exploits,

Reference 39

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source=pdf_text observed=2026-08-01T05:55:24.190644Z digest=sha256:6764139cf7ef1b40de74a8c198a72a159315b47ce21dc82ef1fd25def5a8daad

Observation 4935e060-8164-41eb-88a0-37a0705491f9 · outbound

This paper cites Secbench. js: An executable security benchmark suite for server-side javascript,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Secbench. js: An executable security benchmark suite for server-side javascript,

Reference 40

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source=pdf_text observed=2026-08-01T05:55:24.268617Z digest=sha256:776a1f5eb178f6a17dfc655ab4a015812dcb17f8bab74b42f9416722c348f175

Observation 228a1dfe-f5b0-404c-9103-c285d3ff22d8 · outbound

This paper cites Prompt engineering in llms for automated unit test generation: A large-scale study,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Prompt engineering in llms for automated unit test generation: A large-scale study,

Reference 41

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source=pdf_text observed=2026-08-01T05:55:24.330430Z digest=sha256:6fe0dacec0619314d90f8ee3b0d8da5a26a85a083b0fdc0d87e29369e59ec8c3

Observation ade1adc2-7217-4d4f-9852-3dbb145879a9 · outbound

This paper cites Large language model for vulnerability detection: Emerging results and future directions,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Large language model for vulnerability detection: Emerging results and future directions,

Reference 42

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source=pdf_text observed=2026-08-01T05:55:24.410645Z digest=sha256:07103de42bcfa31e6b7937eeb8a17b32dbfe718b7657b7cd985cd66091e0af15

Observation a02f0d6c-de5c-4923-86a9-0c84d74ab26e · outbound

This paper cites Examining zero-shot vulnerability repair with large language models,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Examining zero-shot vulnerability repair with large language models,

Reference 43

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source=pdf_text observed=2026-08-01T05:55:24.465627Z digest=sha256:7d7838907a15771de3a2fdce367ef702c92f1e4adebf2148b2420dcba959e4e2

Observation a3c15560-a20a-48ad-b45a-0176e0de413a · outbound

This paper cites Regular expression denial of service (ReDoS) in codemir- ror,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Regular expression denial of service (ReDoS) in codemir- ror,

Reference 44

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source=pdf_text observed=2026-08-01T05:55:24.519832Z digest=sha256:cb47f9cc859f6feb0e422fe3160126bf47d3040aed970b0446851d8afcacda94

Observation 8edcbf94-2b3a-43b7-8902-b292f9e1d9a8 · outbound

This paper cites Prototype Pollution in immer,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Prototype Pollution in immer,

Reference 45

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source=pdf_text observed=2026-08-01T05:55:24.602570Z digest=sha256:460475f749474320b503f2febd47fbb1568270185d87164e2e08c28565a4d676

Observation e0196930-d8de-44d7-98c2-fc22ff20505d · outbound

This paper cites Just-in-time defect prediction on javascript projects: A replication study,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Just-in-time defect prediction on javascript projects: A replication study,

Reference 46

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source=pdf_text observed=2026-08-01T05:55:24.678334Z digest=sha256:43ed5d7ad4784dcaff344c8adc568b4f823af9871a451270a4f9ea1abb77463f

Observation be717e5f-db91-4840-8be4-5ad4dc3b222a · outbound

This paper cites Jit-smart: A multi-task learning framework for just-in-time defect prediction and localization,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Jit-smart: A multi-task learning framework for just-in-time defect prediction and localization,

Reference 47

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source=pdf_text observed=2026-08-01T05:55:24.763912Z digest=sha256:73ae2ee1a9db06a16e6e5710f371a90a41deefef1bd850bcc4c3142f61beeb8a

Observation 8ec165c9-24a5-4ca3-9e22-f4f1a0cf4807 · outbound

This paper cites Bridging expert knowledge with deep learning techniques for just-in-time defect prediction,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Bridging expert knowledge with deep learning techniques for just-in-time defect prediction,

Reference 48

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source=pdf_text observed=2026-08-01T05:55:24.817873Z digest=sha256:5411a4ad2a662e2c4d905aa982bf227c1c62b13fe06e3ff17c97a63a61aae81c

Observation 5eb3c1ad-e03d-4dc1-b248-98d989eb71a3 · outbound

This paper cites A large-scale empirical study of just-in-time quality assurance,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution A large-scale empirical study of just-in-time quality assurance,

Reference 49

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source=pdf_text observed=2026-08-01T05:55:24.874163Z digest=sha256:f985aef02cfb4f8d53dc196832782b23f93e517140aa933344a904ddead00a69

Observation 6c42e4a9-be34-4d7e-ace3-1941a9fa30ed · outbound

This paper cites An empirical study of just-in-time defect prediction using cross-project models,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution An empirical study of just-in-time defect prediction using cross-project models,

Reference 50

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source=pdf_text observed=2026-08-01T05:55:24.952369Z digest=sha256:929eee168e25630ab3213da47ae3b8d979e74ed9c31c9a8b1a03ebfb41e97c88

Observation d61e3596-85fa-4775-9c88-b2a0c2e15c00 · outbound

This paper cites Deep just-in-time defect prediction: how far are we?.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Deep just-in-time defect prediction: how far are we?

Reference 51

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source=pdf_text observed=2026-08-01T05:55:25.004959Z digest=sha256:7bed505fa320ee71cacbedf95903d93ef07de9dbfa8043032cf4bd6360cda232

Observation 3cc13c77-49a7-48ec-bdbf-1406c8e42811 · outbound

This paper cites Cc2vec: Distributed representations of code changes,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Cc2vec: Distributed representations of code changes,

Reference 52

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source=pdf_text observed=2026-08-01T05:55:25.082949Z digest=sha256:fcd2f4bc3cf2a10909be41b5f397036c63f1688ddee334b138f478bb3c03fe3d

Observation e49c54d2-96b2-4391-9631-b8a469a6fda8 · outbound

This paper cites Deepjit: an end-to-end deep learning framework for just-in-time defect prediction,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Deepjit: an end-to-end deep learning framework for just-in-time defect prediction,

Reference 53

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source=pdf_text observed=2026-08-01T05:55:25.164442Z digest=sha256:3a33336ed0e89f31adb58239855f8191dd89ac28274d149d2b2ce595f4eaa850

Observation 08ab6cdd-8b0d-4e19-85af-ea367b7b94c9 · outbound

This paper cites Toward realistic evaluations of just-in-time vulnerability prediction,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Toward realistic evaluations of just-in-time vulnerability prediction,

Reference 54

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source=pdf_text observed=2026-08-01T05:55:25.220784Z digest=sha256:7aa3912f6e69cdd1075b71d101cdde4485416e92d1ac7d277c97787a0185b86c

Observation 32791004-5ba9-4f0d-bb01-49d672c06f7b · outbound

This paper cites Vccfinder: Finding potential vulnerabilities in open-source projects to assist code audits,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Vccfinder: Finding potential vulnerabilities in open-source projects to assist code audits,

Reference 55

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source=pdf_text observed=2026-08-01T05:55:25.301796Z digest=sha256:b6450edf0fc5e060ee26fa3db615170038f1f74a7b32f6406b1a45ed68e5bf0b

Observation f9b279da-29e8-48ed-8f2e-5eb9511b18bc · outbound

This paper cites Fine-grained commit-level vulnerability type prediction by cwe tree structure,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Fine-grained commit-level vulnerability type prediction by cwe tree structure,

Reference 56

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source=pdf_text observed=2026-08-01T05:55:25.386666Z digest=sha256:6c89ffed0b5bde816dc01fd66f28bfe404ed5bf6daf2b56943961543a06a987f

Observation 82bbdfc9-e345-4f31-8ad6-a0f79561f1b6 · outbound

This paper cites Commit- level, neural vulnerability detection and assessment,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Commit- level, neural vulnerability detection and assessment,

Reference 57

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source=pdf_text observed=2026-08-01T05:55:25.443332Z digest=sha256:39b6d611cce69de05798f9d552ded0a7bfdcb5ce5f23f8ac20745edbf295c0c9

Observation 34bae5cf-b476-4157-af94-d29b1307051b · outbound

This paper cites Deepcva: automated commit-level vulnerability assessment with deep multi-task learning,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Deepcva: automated commit-level vulnerability assessment with deep multi-task learning,

Reference 58

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source=pdf_text observed=2026-08-01T05:55:25.499664Z digest=sha256:d6bf1f352d68d95dfe81976867fff01494fff1b4126e68d009c88547488100c2

Observation 03adf4a7-29c3-40a0-80db-b7e84a505478 · outbound

This paper cites Testora: Using natural language intent to detect behavioral regressions,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Testora: Using natural language intent to detect behavioral regressions,

Reference 59

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source=pdf_text observed=2026-08-01T05:55:25.582039Z digest=sha256:0f513e66e76ea577785f679a5c03a06de0472e5b7c50b525eb3d9bec273ca05c

Observation b837d5d4-073c-4bed-a608-b377c12cd17c · outbound

This paper cites Pareto prompt optimization,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Pareto prompt optimization,

Reference 60

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source=pdf_text observed=2026-08-01T05:55:25.642778Z digest=sha256:212cab785f766f1985a1db6d679f7bc9874c0c851053b540d21f525789e9dfef

Observation cff2c093-5477-4164-8fca-9589ba41d458 · outbound

This paper cites Metagpt: Meta programming for a multi-agent collaborative framework,.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Metagpt: Meta programming for a multi-agent collaborative framework,

Reference 61

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source=pdf_text observed=2026-08-01T05:55:25.648463Z digest=sha256:0173b916f901a14bcfbd06c7c36e6f4ffe039a5520b19af67c9db214226c0d4f

Observation cdc04542-6869-487b-bf3f-8a1fdbd5eeea · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 62

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source=pdf_text observed=2026-08-01T05:55:25.655192Z digest=sha256:b8d9bf20beaada7eb9a7af9cc279538e6efeab31112871f7a09fccf155cc0fe5

Observation f50f5754-f44c-452b-9a70-2edbb9f94831 · outbound

This paper cites Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding.

PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

Reference 63

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source=pdf_text observed=2026-08-01T05:55:25.661951Z digest=sha256:20caf3a92771a533e0a4b4d55e3b5b5a8f1ff2a36903956108d42e27b6992da4

Pith citing papers

No inbound Pith citation observations are available.