feat: cwe visualization (#3)

* feat: cwe visualization

* Update script/venn4py.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

Author: ganler

requirements.txt

@@ -12,3 +12,4 @@ bandit
 tenacity
 sandbox-fusion
 rich
+matplotlib

script/cwepie.py

@@ -0,0 +1,198 @@
+# SPDX-FileCopyrightText: (c) UIUC PurpCode Team
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import matplotlib.pyplot as plt
+
+# latex required
+plt.rcParams.update(
+    {
+        "text.usetex": True,
+        "font.family": "serif",
+        "font.serif": ["Computer Modern Roman"],
+    }
+)
+
+# Data provided
+data = {
+    "AWS credentials logged": 50,
+    "AWS insecure transmission CDK": 50,
+    "AWS missing encryption CDK": 50,
+    "AWS missing encryption of sensitive data cdk": 50,
+    "Clear text credentials": 50,
+    "Cross-site request forgery": 56,
+    "Cross-site scripting": 147,
+    "Deserialization of untrusted object": 50,
+    "Empty Password": 17,
+    "Garbage collection prevention in multiprocessing": 58,
+    "Hardcoded IP address": 50,
+    "Hardcoded credentials": 144,
+    "Improper authentication": 70,
+    "Improper certificate validation": 44,
+    "Improper input validation": 75,
+    "Improper privilege management": 8,
+    "Improper resource exposure": 70,
+    "Improper sanitization of wildcards or matching symbols": 52,
+    "Insecure CORS policy": 58,
+    "Insecure Socket Bind": 66,
+    "Insecure connection using unencrypted protocol": 83,
+    "Insecure cookie": 64,
+    "Insecure cryptography": 130,
+    "Insecure hashing": 282,
+    "Insecure temporary file or directory": 125,
+    "Integer overflow": 50,
+    "LDAP injection": 54,
+    "Log injection": 82,
+    "Loose file permissions": 241,
+    "Missing Authorization CDK": 50,
+    "Mutually exclusive call": 50,
+    "OS command injection": 1411,
+    "Override of reserved variable names in a Lambda function": 55,
+    "Path traversal": 223,
+    "Public method parameter validation": 273,
+    "Resource leak": 1516,
+    "S3 partial encrypt CDK": 50,
+    "SQL injection": 106,
+    "Socket connection timeout": 109,
+    "Spawning a process without main module": 52,
+    "URL redirection to untrusted site": 70,
+    "Unauthenticated Amazon SNS unsubscribe requests might succeed": 50,
+    "Unauthenticated LDAP requests": 50,
+    "Unrestricted upload of dangerous file type": 70,
+    "Unsafe Cloudpickle Load": 51,
+    "Unsanitized input is run as code": 351,
+    "Untrusted AMI images": 50,
+    "Usage of an API that is not recommended": 17,
+    "Usage of an API that is not recommended - High Severity": 29,
+    "Usage of an API that is not recommended - Medium Severity": 1390,
+    "Using AutoAddPolicy or WarningPolicy": 4,
+    "Weak algorithm used for Password Hashing": 108,
+    "Weak obfuscation of web request": 52,
+    "XML External Entity": 19,
+    "XPath injection": 51,
+    "Zip bomb attack": 56,
+}
+
+
+# Prepare data: Top N and 'Others'
+sorted_data = dict(sorted(data.items(), key=lambda item: item[1], reverse=True))
+top_n_count = 10
+top_n_labels_orig = list(sorted_data.keys())[:top_n_count]
+top_n_freqs = list(sorted_data.values())[:top_n_count]
+top_n_ratio = [(f / sum(sorted_data.values())) for f in top_n_freqs]
+other_size = sum(list(sorted_data.values())[top_n_count:])
+
+# Create legend labels with frequencies
+max_label_length = 64
+plot_labels_for_legend = []
+for i in range(len(top_n_labels_orig)):
+    label_text = top_n_labels_orig[i].split(" - ")[0]
+    freq = top_n_freqs[i]
+    ratio = top_n_ratio[i]
+    if len(label_text) > max_label_length:
+        truncated_label_text = label_text[: max_label_length - 3] + "..."
+    else:
+        truncated_label_text = label_text
+    plot_labels_for_legend.append(f"{truncated_label_text} ({ratio * 100:.1f}\\%)")
+
+# Determine plot_sizes for pie chart and add 'Others' label if needed
+if other_size > 0:
+    plot_labels_for_legend.append(f"Others")  # MODIFIED: Added frequency for Others
+    plot_sizes = top_n_freqs + [other_size]
+else:
+    plot_sizes = top_n_freqs
+
+
+grouped_labels = []
+grouped_counts = []
+others_count = 0
+
+for k, v in sorted_data.items():
+    if v >= 144:
+        grouped_labels.append(k)
+        grouped_counts.append(v)
+    else:
+        others_count += v
+
+grouped_labels.append("Others")
+grouped_counts.append(others_count)
+
+fig, ax = plt.subplots(1, 1, figsize=(10, 6))
+
+
+def make_autopct(values):
+    def my_autopct(pct):
+        return f"{pct:.1f}%"
+
+    return my_autopct
+
+
+# Styling
+fig, ax = plt.subplots(1, 1, figsize=(3.5, 3.5))
+
+# Create a color map
+num_colors = len(plot_sizes)
+colors_palette = [
+    "#f7c59f",  # Soft peach
+    "#ffb58b",  # Warm coral
+    "#ffd48a",  # Pastel amber
+    "#fff0a5",  # Light butter‑yellow
+    "#e9e3a4",  # Sandstone
+    "#d8f0a1",  # Pale pistachio
+    "#c1e8b0",  # Mint‑melon
+    "#b8e8d4",  # Icy aqua
+    "#cde0ff",  # Powder periwinkle
+    "#d8c7ff",  # Lilac
+    "lightgray",
+]
+
+final_colors = [colors_palette[i % len(colors_palette)] for i in range(num_colors)]
+
+wedges, texts, autotexts = ax.pie(
+    plot_sizes,  # This now correctly reflects top N + Others (if any)
+    # autopct="%1.1f\\%%",
+    startangle=140,
+    pctdistance=0.75,
+    colors=final_colors,
+    wedgeprops=dict(width=0.5, edgecolor="w"),
+    textprops={"fontsize": 16},
+    explode=[0.05 if label == "Others" else 0.03 for label in grouped_labels],
+    autopct=make_autopct(grouped_counts),
+)
+
+for val, txt in zip(plot_sizes, autotexts):
+    pct = val / sum(plot_sizes) * 100
+    if pct > 15:
+        txt.set_fontsize(18)
+        txt.set_text(r"\textbf{" + txt.get_text() + r"}")
+
+plt.setp(autotexts, size=11, weight="bold", color="black")
+ax.axis("equal")
+
+plt.subplots_adjust(left=0.1, right=0.85)
+legend = ax.legend(
+    wedges,
+    plot_labels_for_legend,  # This now includes frequencies
+    title="\\textbf{Top CodeGuru Detections}",
+    title_fontsize="12",
+    loc="center left",
+    bbox_to_anchor=(0.95, 0.5),
+    fontsize=11,  # May need to adjust if labels with freq are too long
+    frameon=False,
+    shadow=False,
+)
+
+
+plt.savefig(
+    "cwepie.png",  # New filename
+    bbox_extra_artists=(legend,),
+    bbox_inches="tight",
+    dpi=300,
+    pad_inches=-0.05,  # User's custom padding
+)
+plt.savefig(
+    "cwepie.pdf",  # New filename
+    bbox_extra_artists=(legend,),
+    bbox_inches="tight",
+    pad_inches=-0.05,  # User's custom padding
+)