Fissure Security · Benchmark

Subtext is more accurate and 40× faster than a frontier-model agent.

On a blind 170-file corpus, Subtext caught 100% of threats with zero false alarms. A Claude Opus 4.8 agent, given the same files with full tools and vision, caught about 90%, raised false alarms on a third of the clean files, and took 11 minutes to Subtext's 15 seconds.

170 files · blind (renamed to numbers) 157 scored for detection Subtext by Fissure Security Agent: Claude Opus 4.8, full tools + OCR
The result at a glance
100%
Threats caught
Every one of 111 threats. Opus caught ~90%, so real threats slipped past it.
0
False alarms
Opus wrongly flagged 15 to 19 of 46 clean files, a third of everything benign.
40×
Faster per file
0.09s vs 3.5s, and that is Subtext in Docker on a laptop.
15s
To scan the whole corpus
The Opus agent needed 11 minutes.
Accuracy · vs. known-correct verdicts (111 threats, 46 benign)

Real threats let through

Files that should be blocked but were allowed. Lower is better.

Subtext0
Opus · no-OCR11
Opus · OCR12

False alarms on clean files

Benign files wrongly flagged, of 46. Lower is better.

Subtext0
Opus · no-OCR19
Opus · OCR15
EngineCatch rateThreats missedFalse alarmsPrecisionAccuracy
Subtext100%00 / 46100%100%
Opus 4.8 (no OCR)90.1%1119 / 4684.0%80.9%
Opus 4.8 (OCR)89.2%1215 / 4686.8%82.8%

What counts as a threat

A file is a threat when its actual content, not its name, type, or wrapper, carries something that must not pass a content gate. Three categories:

Data exfiltrationSecrets, credentials, keys, or regulated and bulk PII leaving the organization, including when it is encoded, ciphered, compressed, embedded in a document's internals, or rendered inside an image.
Malicious or active contentExecutables, macros, scripts, serialized-code payloads, or exploit triggers delivered inside documents, archives, or files posing as something benign.
Concealment and evasionTechniques used to smuggle either past inspection: steganography, data appended outside a file's normal structure, type or extension mismatch, deep-nested archives, obfuscation, and hidden markers or links.

Everything else, ordinary business and personal files, is benign and should pass untouched. Threats are defined by what they carry, not by how Subtext detects them; the signals, scoring, and thresholds are proprietary.

What the agent let through

Opus missed one class Subtext catches every time: secrets and PII buried inside document internals. Spreadsheets hid SSNs in chart XML. Word-processing documents carried sensitive data in custom XML parts, table and page footers, and document metadata and comments. Payloads were encoded or ciphered inside the document body rather than its visible text. The agent reads the obvious content; Subtext extracts and scores every embedded part and archive member. Opus also invented steganography in clean images, the bulk of the agent's false alarms.

Speed · same corpus, wall-clock

Total processing time

All 170 files, start to finish. Lower is better.

Subtext · no-OCR15.0 s
Subtext · OCR88.3 s
Opus · no-OCR602 s  ·  10.0 min
Opus · OCR661 s  ·  11.0 min

Files processed per second

Higher is better. The Opus bars are barely visible, which is the point.

Subtext · no-OCR11.35 /s  ·  0.09s/file
Subtext · OCR1.93 /s  ·  0.52s/file
Opus · no-OCR0.28 /s  ·  3.54s/file
Opus · OCR0.26 /s  ·  3.89s/file

Subtext was measured in Docker on a consumer laptop (2 workers). On enterprise hardware it runs faster still, so this 40× gap is a floor, not a ceiling.

Cost · the agent bills for every token
~$0
Subtext per-file cost. Self-hosted, no per-token billing.
$5,220
Opus 4.8 token cost to scan 1,000,000 files
$1.9M/yr
Opus token cost at enterprise volume (1M files/day)

⚑ The agent's accuracy is overstated

Opus was told to judge only by content and never saw the real filenames, yet it wrote: the block_klingon reference from memory suggests these are steganographic/covert. It recalled an original filename the blind set had stripped, so it scored with hints. Its true blind numbers are worse than shown here, which only widens Subtext's lead.

Corpus and ground truth. 170 files renamed to sequential numbers; each file's known-correct verdict is its intended result in Subtext's test suite. 157 carry a threat-detection ground truth (111 should-flag, 46 benign). "Catch rate" is the share of threats flagged (block or review); a "false alarm" is a benign file flagged.

Method. One Opus 4.8 agent per profile (no-OCR, OCR), isolated to a renamed copy of the corpus, full tools and vision. Subtext measured in-process in Docker on a consumer laptop, 2 uvicorn workers, OCR toggled between runs. Cost: Opus 4.8 at $5/$25 per 1M input/output, 90/10 blend; tokens only, a conservative floor.