
LLM System Prompt Security Measures (Conceptual)

Generated output: LLM System Prompt Security Measures (Conceptual) — output 1
This is not an image generation prompt, but a conceptual LLM prompt detailing security measures used by Google Finance, generated by Nano Banana Pro. It outlines various techniques like prompt injection content classifiers, security thought reinforcement, markdown sanitization, and user confirmation frameworks to prevent adversarial attacks and system prompt leakage.
Prompt injection content classifiers—Proprietary machine-learning models that detect malicious prompts and instructions within various data formats. Security thought reinforcement—Targeted security instructions that are added around the prompt content. These instructions remind the LLM (large language model) to perform the user-directed task and ignore adversarial instructions. Markdown sanitization and suspicious URL redaction—Identifying and redacting external image URLs and suspicious links using Google Safe Browsing to prevent URL-based attacks and data exfiltration. User confirmation framework—A contextual system that requires explicit user confirmation for potentially risky operations, such as deleting calendar events. End-user security mitigation notifications—Contextual information provided to users when security issues are detected and mitigated. These notifications encourage users to learn more via dedicated help center articles. Model resilience—The adversarial robustness of Gemini models, which protects them from explicit malicious manipulation.
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Cozy Tech Bedroom Portrait (JSON Format)
Melisa♡Nano Banana Pro
{
"meta": {
"title": "Cozy Tech Bedroom Portrait",
"version": "1.0",
"intent": "Photorealistic Social Media/Lifestyle"
},
"generation_params": {
"aspect_ratio": "4:5",
"width": 1024,
"height": 1280,
"seed": -1,
"steps": 25,
"cfg_scale": 7.0
},
"prompt_components": {
"subject": {
"description": "Girl from reference, matching face exactly",
"hair": "{argument name=\"hair color and style\" default=\"Wet silver grey hair\"}",
"makeup": "Natural soft-glam makeup",
"expression": "Subtle smile"
},
"apparel": {
"clothing": "{argument name=\"clothing\" default=\"Oversized white t-shirt\"}",
"accessories": "None"
},
"pose_and_action": {
"body_position": "Sits cross-legged on a bed",
"interaction": "Laptop in front of her",
"vibe": "Relaxed cozy pose"
},
"environment": {
"setting": "Nighttime bedroom",
"background_elements": "Dark curtains",
"atmosphere": "Modern cozy-tech vibe"
},
"technical_specs": {
"lighting": "Dim ambient lighting, soft harsh flash on face",
"color_grading": "Muted warm tones",
"camera_effects": "Gentle film grain",
"render_quality": "Ultra-realistic, realistic skin texture, clean complexion, crisp detailed rendering"
}
},
"full_concatenated_prompt": "Ultra-realistic nighttime bedroom photo of the same girl from the reference, matching her face exactly, with wet silver grey hair and natural soft-glam makeup. She sits cross-legged on a bed with a laptop in front of her, wearing an oversized white t-shirt. Relaxed cozy pose, subtle smile. Dark curtains, dim ambient lighting, soft harsh flash on her face, gentle film grain, muted warm tones. Modern cozy-tech vibe, realistic skin texture, clean complexion, crisp detailed rendering.",
"negative_prompt": "different face, deformed limbs, messy background, overexposed flash, incorrect laptop text, distortion"
}

Clean infographic style constraints in Japanese
エクセル兄さん(たてばやし淳)@ExcelとChatGPT著書多数Nano Banana Pro
テキストをきわめて少なく、グラフィカルな表現を重視。日本語の文字化けを抑える。フォントはヒラギノゴシック中心。コンテンツはそのままに配色やデザインはMicrosoft365のように。フラットデザインでシンプルに。
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