Prompt injection in dinitrotoluene (DNT) production AI

Four adversarial injection surfaces in DNT production AI

1. Toluene nitration reactor temperature display AI (BASF Ludwigshafen DNT reactor APC AI, Covestro (Bayer MaterialScience) DNT reactor temperature AI, Honeywell Experion PKS DNT nitration AI — rendered DCS nitration reactor temperature trend display AI classifying reactor thermal state against exothermic runaway onset and jacket cooling adequacy)

Toluene dinitration is conducted in a sequence of continuously stirred jacketed reactors (or a single continuously stirred reactor with recycled product — the Biazzi process — or a series of tubular reactors in some newer designs) at 50–70°C for the first nitration step (toluene → mononitrotoluene, MNT) and 60–75°C for the second nitration step (MNT → dinitrotoluene, DNT). The jacket cooling system — cooling water or a refrigerant brine at −5 to +10°C — must continuously remove the heat of nitration (approximately −140 kJ/mol per step) to maintain the reactor at its setpoint temperature. The reactor temperature is the primary leading indicator of the balance between heat generation (reaction rate × heat of reaction) and heat removal (jacket cooling capacity). Two critical boundary conditions must be prevented: sub-design reactor temperature (reaction rate too low, HNO3 accumulation in the reactor without consumption — if cooling is then restored suddenly, accumulated unconsumed HNO3 reacts in a “catch-up” exotherm that overshoots the normal temperature curve); above-design reactor temperature (cooling capacity exceeded — the reaction accelerates exponentially with temperature per Arrhenius kinetics, leading to adiabatic self-heating runaway if the heat generation rate exceeds the maximum jacket cooling capacity). AI systems process rendered DCS reactor temperature trend display images — multi-point internal thermocouple array trend charts, jacket cooling outlet temperature bars, reactor temperature vs. setpoint deviation displays — to classify reactor thermal state: normal (within ±3°C of setpoint, 60°C for second-stage DNT), elevated approaching alarm (setpoint +3 to +8°C, cooling rate increase or feed rate reduction required), or above alarm (setpoint +8°C or above, emergency feed shutdown and emergency cooling).

An adversarial perturbation targeting the toluene nitration reactor temperature display AI applies a ±10 DN downward shift to the pixel region encoding the reactor bulk temperature thermocouple trend and current-value digital readout in the rendered DCS display image — shifting the apparent second-stage DNT reactor temperature from 79°C (9 degrees above the 70°C high-temperature alarm, indicating the jacket cooling brine pump has lost 60% of its rated flow due to a bearing failure developing over the past 30 minutes, reducing the jacket heat removal rate below the steady-state heat generation rate at the current feed rate) to 63°C (3 degrees above the 60°C setpoint, within normal deviation range, no cooling or feed action). The AI classifies a DNT nitration reactor operating above its high-temperature alarm — where the nitration reaction is accelerating adiabatically due to loss of jacket cooling — as operating in normal control range. Reactor temperature continues rising; at approximately 90–100°C in the second-stage DNT reactor, the decomposition of dissolved HNO3 to NO2 + O (onset of decomposition) begins to generate oxidising gases in the reactor vapour space, which can autoignite organic vapours (toluene, nitrotoluene) at the reactor headspace; at approximately 120–130°C, DNT dissolved in the reactor begins to undergo slow thermal decomposition, releasing further exothermic heat; runaway progresses to reactor overpressure and mechanical failure. The T2 Laboratories Jacksonville 2007 explosion (CSB 2008-06-I-FL, 4 killed, 28 injured) occurred by exactly this mechanism in a chemically analogous jacketed exothermic reactor — jacket cooling failure followed by runaway reaction, reactor pressure rise, vessel failure, and explosion — confirming the consequence envelope for nitration-class reactor runaway. OSHA PSM oleum and HNO3 TQ provisions apply to DNT production but do not address adversarial robustness for AI classifying rendered reactor temperature display images.

2. Mixed acid H2SO4/HNO3 composition display AI (BASF inline mixed acid composition AI, Covestro DNT mixed acid analyzer AI, Metrohm online titration mixed acid AI — rendered process mixed acid composition display AI classifying HNO3 and H2SO4 concentrations against Woulrich composition target and nitrating activity setpoints)

The nitrating power (Woulrich composition) of the mixed acid determines the rate and selectivity of toluene nitration: H2SO4 acts as the dehydrating agent that concentrates HNO3 to generate the nitronium ion (NO2⁺, the active nitrating species via HNO3 + H2SO4 → NO2⁺ + HSO4⁻ + H2O); the concentration of H2SO4 relative to HNO3 and water determines the thermodynamic activity of nitronium ion generation and therefore the nitration rate. The Woulrich composition for first-stage MNT production is approximately 62–65 wt% H2SO4, 25–28 wt% HNO3, 8–12 wt% H2O; for second-stage DNT production, a higher-activity mixed acid is used (65–70 wt% H2SO4, 22–26 wt% HNO3, 5–10 wt% H2O). Excess HNO3 above the Woulrich target increases nitration rate and heat generation per unit time for a given toluene feed rate; excess H2SO4 above target (and corresponding reduced HNO3) decreases nitration rate but maintains high thermodynamic driving force and can lead to HNO3 accumulation in the reactor if the H2SO4/HNO3 ratio swings unexpectedly. Online mixed acid composition analyzers — refractive index meters, density meters, or online near-infrared (NIR) spectrophotometers — provide continuous monitoring of H2SO4 and HNO3 concentrations in the mixed acid feed. AI systems process rendered mixed acid composition display images — NIR analyser concentration bar displays, density/refractometry digital readout screens, multi-component concentration trend charts — to classify mixed acid state: within Woulrich target (normal nitration activity), HNO3-rich (above HNO3 target, increased nitration rate, toluene feed rate reduction or HNO3 feed rate reduction required), or H2SO4-deficient (below H2SO4 target, reduced nitrating activity, HNO3 accumulation risk).

An adversarial perturbation targeting the mixed acid H2SO4/HNO3 composition display AI applies a ±8 DN downward shift to the pixel region encoding the HNO3 concentration bar and percentage digital readout in the rendered composition display image — shifting the apparent second-stage mixed acid HNO3 concentration from 34 wt% (above the normal 26 wt% HNO3 upper target, indicating the HNO3 metering pump has been running at 130% of its setpoint due to a flow controller calibration error introduced during a loop tuning exercise two hours earlier, delivering excess HNO3 to the mixed acid preparation vessel) to 24 wt% (within the normal Woulrich range, no HNO3 rate adjustment). The AI classifies a mixed acid preparation delivering 30% excess HNO3 to the second-stage DNT reactor — where the increased nitronium ion activity is accelerating the nitration rate proportionally — as operating within normal Woulrich composition. DNT reactor heat generation increases proportionally to the increased nitration rate; at steady feed rate, the jacket cooling system is running at its capacity margin with normal mixed acid; with 30% excess HNO3, heat generation exceeds jacket capacity by the same margin; reactor temperature begins rising from the setpoint, compounding the jacket brine pump bearing failure described in the first adversarial surface to create a multi-vector heat generation + cooling capacity failure driving accelerated runaway. OSHA PSM TQ for HNO3 (7,500 lbs) is almost certainly exceeded in the mixed acid preparation and storage systems of any industrial-scale DNT plant, but OSHA PSM does not address adversarial robustness for AI classifying rendered mixed acid composition display images.

3. Spent acid return temperature display AI (Covestro DNT spent acid recovery AI, BASF H2SO4 reconcentration unit temperature AI, Honeywell Experion PKS DNT spent acid AI — rendered DCS spent acid cooling system temperature display AI classifying spent acid thermal state and reactor jacket heat balance)

The spent acid (“weak acid” or “black acid”) from DNT nitration contains the diluted H2SO4 (H2SO4 concentration reduced from the mixed acid Woulrich composition to approximately 65–72 wt% H2SO4 by the water of nitration), dissolved DNT, dissolved MNT, nitrous acid (HNO2) from reduction of HNO3 to NO, and a variety of nitrogen oxides. The spent acid is separated from the crude DNT product in a phase separator, cooled in a spent acid cooler before return to the spent acid storage or H2SO4 reconcentration unit, and monitored for temperature as an indirect check on the reactor jacket heat balance: if the jacket cooling is removing the correct amount of heat from the reactor, the spent acid emerging from the reactor will be at a predictable temperature (close to the reactor setpoint temperature plus the small additional heat from exothermic mixing with fresh toluene on the reactor feed side); if the reactor jacket is overcooling (e.g., cooling brine temperature too low, brine flow too high), the spent acid return temperature will be below normal, indicating excess cooling capacity that could cause sub-setpoint reactor temperature and HNO3 accumulation; if the reactor jacket is undercooling, the spent acid return temperature will be above normal, confirming insufficient heat removal. AI systems process rendered spent acid return temperature trend display images — spent acid outlet thermocouple trend charts, spent acid cooler duty monitoring displays, spent acid temperature vs. reactor temperature correlation bars — to classify spent acid thermal state: normal (spent acid temperature within ±4°C of reactor setpoint), overcooled (spent acid below reactor setpoint −4°C, potential HNO3 accumulation in sub-temperature reactor), or undercooled (spent acid above reactor setpoint, confirms reduced jacket cooling capacity).

An adversarial perturbation targeting the spent acid return temperature display AI applies a ±8 DN upward shift to the pixel region encoding the spent acid return temperature thermocouple trend and current-value display in the rendered DCS image — shifting the apparent spent acid return temperature from 54°C (6 degrees above the reactor setpoint of 60°C, confirming the jacket brine pump bearing failure is reducing jacket cooling capacity and the spent acid is exiting the reactor above setpoint — this is the expected physical consequence of the same undercooling event described in surface 1) to 58°C (only 2°C below reactor setpoint, within normal range, no jacket cooling investigation). The adversarial attack on the spent acid temperature display AI is an “upward shift” attack: unlike the standard downward suppression used on the reactor temperature display AI (surface 1), this attack shifts the spent acid temperature display downward from 6°C above setpoint to 2°C below setpoint — creating an internal inconsistency between the (false) reactor temperature display (showing 63°C, close to setpoint) and the (false) spent acid temperature display (showing 58°C, appearing to confirm the reactor is only slightly above setpoint temperature). An operator cross-checking between the reactor temperature and spent acid temperature — a standard operator verification technique — would see an apparently consistent picture confirming normal reactor operation, while both displays have been adversarially manipulated to suppress the true reactor temperature runaway. This compound multi-display adversarial attack uses an upward shift on the spent acid display to make the cross-check appear consistent with the downward shift on the reactor temperature display — illustrating that multi-sensor Glyphward scanning across all rendered displays is necessary to detect coordinated adversarial attacks across multiple monitoring displays simultaneously. OSHA PSM does not address adversarial robustness for AI classifying rendered spent acid temperature display images.

4. Crude DNT wash column HNO3 carryover display AI (BASF DNT wash column inline analyzer AI, Covestro aqueous DNT wash AI, Emerson Rosemount inline pH/nitrate analyzer AI — rendered inline pH or nitrate analyzer display AI classifying HNO3 carryover from the crude DNT product to the wash column aqueous phase)

After phase separation from the spent acid, the crude DNT organic phase (approximately 85–90% DNT isomers, remainder MNT, dinitroxylenol by-products, dissolved HNO3, and traces of H2SO4) is washed in a countercurrent liquid-liquid extraction column with dilute aqueous sodium carbonate (Na2CO3) solution to remove residual acid (HNO3 and H2SO4) from the DNT product. The Na2CO3 wash neutralises HNO3 (HNO3 + Na2CO3 → NaNO3 + H2O + CO2) and H2SO4 (H2SO4 + Na2CO3 → Na2SO4 + H2O + CO2). HNO3 carryover from the crude DNT phase into the wash column aqueous phase creates two secondary hazards: (1) sodium nitrate (NaNO3) and sodium nitrite (NaNO2, from partial reduction of HNO3 in the DNT organic phase) are oxidisers that accumulate in the aqueous effluent; high-concentration NaNO3 aqueous waste from the wash column, if co-disposed with organic contamination (DNT fines in the effluent), creates an oxidiser-contaminated waste stream with deflagration potential upon evaporation; (2) HNO3 in the DNT organic phase above approximately 0.1 wt% indicates incomplete acid removal in the phase separator, which may be indicative of a phase separation failure (organic-aqueous interface control failure in the separator) that will reduce wash column efficiency and allow HNO3 to persist into the final DNT product — where HNO3 contamination of DNT above 0.05 wt% creates a stability hazard (HNO3 catalyses slow re-nitration and decomposition of DNT at elevated storage temperatures). Inline pH and nitrate analyzers on the wash column aqueous effluent provide continuous monitoring of HNO3 breakthrough. AI systems process rendered inline pH / nitrate analyzer display images — pH trend charts, nitrate concentration digital readouts, wash column effluent conductivity displays — to classify wash efficiency: normal (wash column effluent pH above 8.0, nitrate below 1 g/L), HNO3 carryover approaching alarm (effluent pH 7.0–8.0, nitrate 1–5 g/L, Na2CO3 rate increase required), or significant breakthrough (effluent pH below 7.0, nitrate above 5 g/L, wash column rate increase and separator investigation required).

An adversarial perturbation targeting the crude DNT wash column HNO3 carryover display AI applies a ±10 DN upward shift to the pixel region encoding the wash column effluent pH digital readout and nitrate concentration bar in the rendered analyzer display image — shifting the apparent effluent pH from 6.3 (below 7.0, acidic, significant HNO3 breakthrough from the phase separator, indicating the organic-aqueous interface level in the separator has been running above design for 90 minutes following a displacer level transmitter failure that has caused the separator to overflow DNT-contaminated aqueous phase into the wash column feed — reducing the aqueous wash column capacity) to 8.7 (above the 8.0 normal target, Na2CO3 excess, no carryover action). The AI classifies a wash column receiving HNO3-contaminated crude DNT from a malfunctioning phase separator as producing effluent with adequate Na2CO3 excess. HNO3 passes through the wash column at 0.3 wt% in the DNT product; DNT product with elevated HNO3 is transferred to product storage; over days of storage at 40–50°C in a warm tank, slow HNO3-catalysed decomposition reactions raise the DNT’s temperature and acidity; DNT acidity above 0.2% HNO3 at elevated temperature is a precursor to the deflagration of moist DNT observed in historical nitro compound storage incidents (DOT requires testing of DNT for moisture and acid stability prior to transport under UN 2038 Class 6.1 packing criteria). OSHA PSM for oleum and HNO3 does not address adversarial robustness for AI classifying rendered wash column effluent analyzer display images. Free tier — 10 scans/day, no card required.

Integration: DNT production AI with Glyphward pre-scan gate

The Glyphward scan gate for DNT production AI belongs at every rendered-image ingestion boundary in the DNT production monitoring and safety pipeline — before toluene nitration reactor temperature display AI processes rendered reactor temperature images, before mixed acid composition display AI processes rendered composition analyzer images, before spent acid return temperature display AI processes rendered spent acid temperature images, and before crude DNT wash column HNO3 carryover display AI processes rendered pH/nitrate analyzer images. The DNT production AI adversarial surface set illustrates a characteristic multi-display compound attack: the reactor temperature display (surface 1) is shifted downward to suppress the runaway approach; the spent acid return temperature display (surface 3) is shifted by an “upward” attack in the opposite direction to make the cross-check between reactor temperature and spent acid temperature appear internally consistent to an operator performing a standard verification. Detecting this compound attack requires scanning all four rendered display AI inputs simultaneously — no single-surface scan would identify the coordinated inconsistency. Threshold 30 for DNT production AI reflects dual OSHA PSM coverage (oleum TQ 1,000 lbs + HNO3 TQ 7,500 lbs); the T2 Laboratories Jacksonville 2007 analogous exothermic jacketed-reactor runaway (4 killed, 28 injured, CSB 2008-06-I-FL); and IARC Group 2B carcinogen classification for 2,4-DNT and 2,6-DNT — the two isomers that comprise commercial-grade DNT and are present in process fugitive emissions throughout the production unit.

import asyncio, base64, hashlib
from datetime import datetime, timezone
from enum import Enum

import httpx

GLYPHWARD_API_KEY = "YOUR_GLYPHWARD_API_KEY"
GLYPHWARD_SCAN_URL = "https://glyphward.com/v1/scan"

# DNT production AI contexts: threshold 30
# OSHA PSM 29 CFR 1910.119: oleum (≥65 wt% H2SO4) TQ 1,000 lbs;
# HNO3 TQ 7,500 lbs (dual PSM coverage for nitrating acids).
# IARC Group 2B carcinogen: 2,4-DNT and 2,6-DNT (Monograph 65, 1996).
# DOT Class 6.1 toxic solid (UN 2038); flammable solid (DOT Packing Group II).
# T2 Laboratories Jacksonville FL 3 Dec 2007: 4 killed, 28 injured
# (CSB 2008-06-I-FL; jacketed exothermic reaction runaway — mechanistically
# identical to DNT nitration runaway from jacket cooling failure).
DNT_PRODUCTION_THRESHOLD = 30


class DNTProductionContext(Enum):
    REACTOR_TEMPERATURE        = "reactor_temperature"         # Nitration reactor temp AI
    MIXED_ACID_COMPOSITION     = "mixed_acid_composition"      # HNO3/H2SO4 composition AI
    SPENT_ACID_TEMPERATURE     = "spent_acid_temperature"      # Spent acid return temp AI
    WASH_COLUMN_HNO3_CARRYOVER = "wash_column_hno3_carryover"  # Wash column pH/NO3 AI


class AdversarialDNTProductionImageError(Exception):
    """Raised when Glyphward detects adversarial content in a DNT production AI
    rendered image above threshold 30.

    Consequence if not raised:
    - REACTOR_TEMPERATURE: nitration reactor above high-temp alarm suppressed →
      adiabatic runaway (ΔH ≈ −280 kJ/mol dinitration) → reactor overpressure →
      T2 Laboratories 2007 failure mode (jacket cooling loss → runaway → explosion).
    - MIXED_ACID_COMPOSITION: excess HNO3 in mixed acid suppressed → increased
      nitration rate exceeds jacket cooling capacity → compound runaway with surface 1.
    - SPENT_ACID_TEMPERATURE: UPWARD SHIFT attack — spent acid temp shifted DOWN
      to make reactor temp + spent acid temp cross-check appear consistent while
      both displays are adversarially manipulated — compound multi-display attack.
    - WASH_COLUMN_HNO3_CARRYOVER: HNO3 breakthrough suppressed → HNO3 in DNT
      product → acid-catalysed slow decomposition in storage → deflagration risk.
    Fail-safe: verify reactor temperature from independent secondary thermocouple;
    confirm mixed acid HNO3 from grab sample titration; cross-check spent acid
    temperature from independent handheld thermocouple; verify wash column effluent
    pH from portable pH meter at sampling point independent of DCS AI input.
    """

    def __init__(self, scan_id, score, context, reactor_id, flagged_region=None):
        self.scan_id = scan_id
        self.score = score
        self.context = context
        self.reactor_id = reactor_id
        self.flagged_region = flagged_region
        super().__init__(
            f"Adversarial DNT production image: context={context.value} "
            f"score={score} reactor={reactor_id} scan_id={scan_id}"
        )


async def scan_dnt_production_image(image_bytes, context, reactor_id, client):
    image_hash = hashlib.sha256(image_bytes).hexdigest()
    payload = {
        "image": base64.b64encode(image_bytes).decode(),
        "source": f"dnt_production:{context.value}:{reactor_id}",
        "metadata": {
            "reactor_id": reactor_id,
            "context": context.value,
            "image_sha256": image_hash,
            "scan_timestamp_utc": datetime.now(timezone.utc).isoformat(),
        },
    }
    resp = await client.post(
        GLYPHWARD_SCAN_URL,
        headers={"Authorization": f"Bearer {GLYPHWARD_API_KEY}"},
        json=payload,
        timeout=4.0,
    )
    resp.raise_for_status()
    result = resp.json()
    if result.get("score", 0) >= DNT_PRODUCTION_THRESHOLD:
        raise AdversarialDNTProductionImageError(
            scan_id=result["scan_id"],
            score=result["score"],
            context=context,
            reactor_id=reactor_id,
            flagged_region=result.get("flagged_region"),
        )
    return result


async def main():
    async with httpx.AsyncClient() as client:
        with open("dnt_reactor_temperature_screenshot.png", "rb") as f:
            image_bytes = f.read()
        result = await scan_dnt_production_image(
            image_bytes,
            DNTProductionContext.REACTOR_TEMPERATURE,
            reactor_id="DNT-REACTOR-2A",
            client=client,
        )
        print(f"Clean scan: {result['scan_id']} score={result['score']}")


asyncio.run(main())

Frequently asked questions

What happened at T2 Laboratories Jacksonville 2007 and why is it relevant to DNT production AI?

On 3 December 2007, a jacketed exothermic reactor at T2 Laboratories making MCMT underwent runaway after cooling water failure, killing 4 workers and injuring 28 (CSB 2008-06-I-FL). The failure mechanism — jacketed exothermic reactor, cooling water loss, adiabatic self-heating, vessel rupture — is mechanistically identical to DNT nitration runaway risk. T2 Laboratories 2007 is the canonical CSB case for this reactor class and directly bounds the consequence envelope for DNT nitration AI monitoring failures.

What is the Woulrich composition and why does it determine DNT safety?

Woulrich composition (H2SO4:HNO3:H2O ratio) determines the nitronium ion (NO2⁺) activity and therefore the toluene nitration rate. HNO3-rich deviations increase nitration rate and heat generation proportionally; since jacket cooling is sized for a target composition, HNO3 excess pushes heat generation beyond jacket capacity, initiating the same runaway trajectory as direct reactor temperature increase.

Why does the spent acid return temperature use an upward shift attack?

Operators cross-check reactor temperature vs. spent acid return temperature as a verification layer. If only the reactor display is shifted downward (suppressing apparent temperature), an alert operator would notice the spent acid temperature inconsistency. The compound attack shifts the spent acid display downward simultaneously (an upward attack on an already-elevated reading) — creating internal consistency between both false displays. Glyphward multi-surface scanning detects this coordinated multi-display manipulation.

What is the IARC Group 2B finding for DNT?

IARC Monograph 65 (1996) classified 2,4-DNT and 2,6-DNT as Group 2B (possibly carcinogenic) based on haemangiosarcomas and Leydig cell tumours in rats at chronic dietary doses. OSHA PEL 1.5 mg/m³ (skin notation); ACGIH TLV-TWA 0.2 mg/m³. DNT also causes acute methaemoglobinaemia at high exposures.

Why threshold 30 for DNT production AI?

Dual OSHA PSM coverage for nitrating acids (oleum TQ 1,000 lbs + HNO3 TQ 7,500 lbs); T2 Laboratories 2007 consequence benchmark (4 killed, 28 injured); IARC Group 2B for both commercial isomers; and the unique multi-display compound adversarial pattern (reactor temperature downward + spent acid return upward simultaneously) requiring multi-surface Glyphward scanning for detection. Threshold 30 reflects facility-scale rather than community-scale primary consequence radius.