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Paper Citation Record · LEDGER

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation

As of 22 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2412.16135.

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

pith.paper-citation-record.v1
2412.16135 v3

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:48:53.553563Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:57:58.244617Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T12:16:17.039197Z

Reference resolution

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b062328c-abd6-418f-b83c-0678a9d4b009 · outbound

This paper cites In 2018 13th International Conference on Malicious and Unwanted Software (MALWARE), 1–10.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In 2018 13th International Conference on Malicious and Unwanted Software (MALWARE), 1–10

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.894966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.451691Z digest=sha256:95790bb0d99c3d6140e9fd3d7163002e87eabaef50c00530a39d49fbca26907c

Observation f4f74590-04a7-4853-9631-8017ff85e09b · outbound

This paper cites Large Language Models for Software Engineering: A Systematic Literature Review.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation Large Language Models for Software Engineering: A Systematic Literature Review

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.457222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.457222Z digest=sha256:86185bd7aba17c20076e2998c4f73c31c589c9ee12aa4f5d754c58f77f073178

Observation 64018eb1-b2be-409e-87ae-4823aa01c52b · outbound

This paper cites In 2018 26th European Signal Processing Con- ference (EUSIPCO), 533–537.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In 2018 26th European Signal Processing Con- ference (EUSIPCO), 533–537

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.863988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.466362Z digest=sha256:76484e02b2206cbcd09bd8d4c328eeaad2f4478ae922b2bf4bda10973b28c66c

Observation 502cd4ad-9bf6-44b9-a3a3-20be1035aa5b · outbound

This paper cites https://mistral.ai/news/codestral/.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation https://mistral.ai/news/codestral/

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.816226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.486218Z digest=sha256:ca2a6eb1ef0d2ddec5b2e65eff281d45539368a2183009bbd39e64ee9873a648

Observation 27d0146c-0b7c-4264-be80-80ea2a7c6840 · outbound

This paper cites https: //furalabs.com/blog/2023/02/12/intro to smt analysis.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation https: //furalabs.com/blog/2023/02/12/intro to smt analysis

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.801171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.490461Z digest=sha256:4c6076abfbf1a7611f28df22933c2223f24984ce5fccef4500054a5717d5fb44

Observation 9bd19c96-6af7-415e-ac96-1452f430c840 · outbound

This paper cites OctoPack: Instruction Tuning Code Large Language Models.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation OctoPack: Instruction Tuning Code Large Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.494619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.494619Z digest=sha256:851bb397c4e893d2b3095280583a183e8dcddd9ae3f7caf2126317d81e3e91a7

Observation 67791a33-4505-4c2c-947d-cecadc7d796c · outbound

This paper cites In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 7777–7791.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 7777–7791

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.787327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.499297Z digest=sha256:4e6fa1d766d2fbd469aed4a4c65f98be5af0d26e8d7660ad3394f69e31ec05d5

Observation 5037b302-84de-497a-876c-12f51201a04d · outbound

This paper cites https://platform.openai.com/docs/ models/gpt-4o.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation https://platform.openai.com/docs/ models/gpt-4o

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.773333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.503274Z digest=sha256:ea694f88f9e02598af36731bb191fddbb9efc1e3edd1475f532d30196e3666f8

Observation 6cc8dc14-abcb-4ab0-a01f-988eace819ce · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation Code Llama: Open Foundation Models for Code

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.507613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.507613Z digest=sha256:530332a384f152f8bf2728dfc2561455b3feb19fde0eb0af400e5dd7b3894ffb

Observation 4c7d43eb-9024-4b24-b97e-7ea54967a3e9 · outbound

This paper cites CodeGemma: Open Code Models Based on Gemma.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation CodeGemma: Open Code Models Based on Gemma

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.513302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.513302Z digest=sha256:9087157bd3fd8b445cf5e8ede6bdd9200122e6519d37b76580540d5e0e249555

Observation b1d65818-e18f-4cdc-b396-3def8c9a92fe · outbound

This paper cites In Machine Learning and Knowledge Discov- ery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part I, 270–285.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In Machine Learning and Knowledge Discov- ery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part I, 270–285

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.752141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.525127Z digest=sha256:808a478a576f34c13a3850c309f8f8e10c6b2fe611f5cf70dec177e9fa794d29

Observation ec99f6c3-c822-4c21-ba21-c66ab9b8de43 · outbound

This paper cites Revisiting Unnaturalness for Automated Program Repair in the Era of Large Language Models.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation Revisiting Unnaturalness for Automated Program Repair in the Era of Large Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.541454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.541454Z digest=sha256:ae3b56133ee712b0afe99bccaa6004a1d53b6b4af2db77d556d98f88c4427417

Observation 4af83780-732f-4027-af92-59821f036605 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.553563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.553563Z digest=sha256:231e488b1838fafddf6c8f1720989a2a66cfb650561762891f7191b1053c62a9

Observation 8bd69e55-9af5-447e-8cb3-6dbc5eec4554 · outbound

This paper cites In Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop , AISec ’14, 27–36.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop , AISec ’14, 27–36

Reference 2014

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.922487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.437835Z digest=sha256:a9e4082440c102af687ab43957e9e38463fe79cf49771e79434c38b5dde940ae

Observation 4e03d8d4-7188-402a-9a7a-20bc39a5e193 · outbound

This paper cites In 2015 ieee/acm 1st international workshop on software pro- tection, 3–9.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In 2015 ieee/acm 1st international workshop on software pro- tection, 3–9

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.880154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.462132Z digest=sha256:f973682d2064bb5c7bf6d039082a8be193b9803650388c71b4fed9173f92ae1f

Observation 76c7a93b-5a02-43c6-85cd-4587eff25116 · outbound

This paper cites In Proceed- ings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, CCS ’18, 2154–2156.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In Proceed- ings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, CCS ’18, 2154–2156

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.907931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.445972Z digest=sha256:ef3405ebcd587c6607d6e363af575072921e7e985fbab8d564b89538b8dfc6bb

Observation 20d7e720-938d-4075-b491-8b4ba953a36b · outbound

This paper cites In 2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), 37–49.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In 2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), 37–49

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.846645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.470484Z digest=sha256:28d6586a5497bcfba806187373ce989c8a11762b2c9adda1bc071de2bb95674e

Observation fde72e94-5f07-4963-b4c9-28dbc6d47c53 · outbound

This paper cites In 2020 International Conference on Emerging Smart Computing and Informatics (ESCI), 52–59.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation In 2020 International Conference on Emerging Smart Computing and Informatics (ESCI), 52–59

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.936433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.432818Z digest=sha256:ae3ee17a193aaab00b7feafc8850e042067db77d31d784405bdec726d76869cc

Observation 94c6cb11-6aac-4da9-a2ea-ad30082989e5 · outbound

This paper cites CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.518639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.518639Z digest=sha256:26b3c731103bce2888ece0de997f17fb4d16ed7fdfa58a0101440ab9bd63ae5f

Observation 5ca33392-e1b1-4c40-82a2-969a25fcac7a · outbound

This paper cites GPT-4 Technical Report.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation GPT-4 Technical Report

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T10:48:53.427329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:48:53.427329Z digest=sha256:7ef3e67abe36ebd3d19bdb545706a0e8908efa9d2937960525da7f5cdf7ad8ff

Observation aeea94d0-f90a-44b4-817c-f9d0b28fd61c · outbound

This paper cites https://ai.meta.com/blog/ meta-llama-3-1/.

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation https://ai.meta.com/blog/ meta-llama-3-1/

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:48:53.831403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T10:48:53.481204Z digest=sha256:5af60c0e91dea1d70bb13526a51acfb990892e91d2547a3ad7746f384da8e8c3

Pith citing papers

Observation 863070b8-df13-45e1-b134-5da399b0505a · inbound

JailbreaksOverTime: Detecting Jailbreak Attacks Under Distribution Shift cites this paper.

JailbreaksOverTime: Detecting Jailbreak Attacks Under Distribution Shift Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-16T05:57:58.620880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:57:58.244617Z digest=sha256:e033741825c684c373786716d81bb0d7415bd81f1d817dbaf99a9f0efdbae91e